diff --git a/.github/workflows/docker.yml b/.github/workflows/docker.yml index cabfe07..207016d 100644 --- a/.github/workflows/docker.yml +++ b/.github/workflows/docker.yml @@ -5,7 +5,9 @@ on: push: branches: - stable - + tags: + - v* + jobs: push_to_registry: diff --git a/Ch02-statlearn-lab.Rmd b/Ch02-statlearn-lab.Rmd index 556bbbf..67c88ef 100644 --- a/Ch02-statlearn-lab.Rmd +++ b/Ch02-statlearn-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch02-statlearn-lab.ipynb b/Ch02-statlearn-lab.ipynb index f137f1c..9f202fe 100644 --- a/Ch02-statlearn-lab.ipynb +++ b/Ch02-statlearn-lab.ipynb @@ -102,10 +102,10 @@ "id": "9e8aa21f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.654555Z", - "iopub.status.busy": "2023-08-21T03:36:04.654242Z", - "iopub.status.idle": "2023-08-21T03:36:04.664431Z", - "shell.execute_reply": "2023-08-21T03:36:04.663990Z" + "iopub.execute_input": "2023-08-22T06:59:05.520475Z", + "iopub.status.busy": "2023-08-22T06:59:05.520373Z", + "iopub.status.idle": "2023-08-22T06:59:05.524957Z", + "shell.execute_reply": "2023-08-22T06:59:05.524661Z" } }, "outputs": [ @@ -135,10 +135,10 @@ "id": "d62ec119", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.666908Z", - "iopub.status.busy": "2023-08-21T03:36:04.666727Z", - "iopub.status.idle": "2023-08-21T03:36:04.693658Z", - "shell.execute_reply": "2023-08-21T03:36:04.693389Z" + "iopub.execute_input": "2023-08-22T06:59:05.526569Z", + "iopub.status.busy": "2023-08-22T06:59:05.526459Z", + "iopub.status.idle": "2023-08-22T06:59:05.528480Z", + "shell.execute_reply": "2023-08-22T06:59:05.528197Z" } }, "outputs": [], @@ -160,10 +160,10 @@ "id": "c64e9f4d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.695168Z", - "iopub.status.busy": "2023-08-21T03:36:04.695071Z", - "iopub.status.idle": "2023-08-21T03:36:04.697996Z", - "shell.execute_reply": "2023-08-21T03:36:04.697736Z" + "iopub.execute_input": "2023-08-22T06:59:05.530498Z", + "iopub.status.busy": "2023-08-22T06:59:05.530245Z", + "iopub.status.idle": "2023-08-22T06:59:05.533462Z", + "shell.execute_reply": "2023-08-22T06:59:05.533113Z" } }, "outputs": [ @@ -200,10 +200,10 @@ "id": "9abccc1f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.699502Z", - "iopub.status.busy": "2023-08-21T03:36:04.699420Z", - "iopub.status.idle": "2023-08-21T03:36:04.701419Z", - "shell.execute_reply": "2023-08-21T03:36:04.701183Z" + "iopub.execute_input": "2023-08-22T06:59:05.535049Z", + "iopub.status.busy": "2023-08-22T06:59:05.534962Z", + "iopub.status.idle": "2023-08-22T06:59:05.537010Z", + "shell.execute_reply": "2023-08-22T06:59:05.536734Z" } }, "outputs": [ @@ -249,10 +249,10 @@ "id": "802ca33c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.702877Z", - "iopub.status.busy": "2023-08-21T03:36:04.702786Z", - "iopub.status.idle": "2023-08-21T03:36:04.704849Z", - "shell.execute_reply": "2023-08-21T03:36:04.704596Z" + "iopub.execute_input": "2023-08-22T06:59:05.538667Z", + "iopub.status.busy": "2023-08-22T06:59:05.538580Z", + "iopub.status.idle": "2023-08-22T06:59:05.541098Z", + "shell.execute_reply": "2023-08-22T06:59:05.540721Z" } }, "outputs": [ @@ -290,10 +290,10 @@ "id": "a8c72744", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.706312Z", - "iopub.status.busy": "2023-08-21T03:36:04.706207Z", - "iopub.status.idle": "2023-08-21T03:36:04.708359Z", - "shell.execute_reply": "2023-08-21T03:36:04.708116Z" + "iopub.execute_input": "2023-08-22T06:59:05.542902Z", + "iopub.status.busy": "2023-08-22T06:59:05.542804Z", + "iopub.status.idle": "2023-08-22T06:59:05.545269Z", + "shell.execute_reply": "2023-08-22T06:59:05.544991Z" } }, "outputs": [ @@ -364,10 +364,10 @@ "id": "f1c7d1db", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.709873Z", - "iopub.status.busy": "2023-08-21T03:36:04.709781Z", - "iopub.status.idle": "2023-08-21T03:36:04.767425Z", - "shell.execute_reply": "2023-08-21T03:36:04.766663Z" + "iopub.execute_input": "2023-08-22T06:59:05.546995Z", + "iopub.status.busy": "2023-08-22T06:59:05.546897Z", + "iopub.status.idle": "2023-08-22T06:59:07.928068Z", + "shell.execute_reply": "2023-08-22T06:59:07.927627Z" }, "lines_to_next_cell": 0 }, @@ -400,10 +400,10 @@ "id": "e2ea2bfd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.772015Z", - "iopub.status.busy": "2023-08-21T03:36:04.771631Z", - "iopub.status.idle": "2023-08-21T03:36:04.777911Z", - "shell.execute_reply": "2023-08-21T03:36:04.777302Z" + "iopub.execute_input": "2023-08-22T06:59:07.930503Z", + "iopub.status.busy": "2023-08-22T06:59:07.930338Z", + "iopub.status.idle": "2023-08-22T06:59:07.932349Z", + "shell.execute_reply": "2023-08-22T06:59:07.932076Z" }, "lines_to_next_cell": 0 }, @@ -439,10 +439,10 @@ "id": "59fbf9fd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.781791Z", - "iopub.status.busy": "2023-08-21T03:36:04.781430Z", - "iopub.status.idle": "2023-08-21T03:36:04.788256Z", - "shell.execute_reply": "2023-08-21T03:36:04.787586Z" + "iopub.execute_input": "2023-08-22T06:59:07.934561Z", + "iopub.status.busy": "2023-08-22T06:59:07.934430Z", + "iopub.status.idle": "2023-08-22T06:59:07.936902Z", + "shell.execute_reply": "2023-08-22T06:59:07.936605Z" }, "lines_to_next_cell": 0 }, @@ -486,10 +486,10 @@ "id": "2279437e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.792995Z", - "iopub.status.busy": "2023-08-21T03:36:04.792549Z", - "iopub.status.idle": "2023-08-21T03:36:04.800387Z", - "shell.execute_reply": "2023-08-21T03:36:04.799738Z" + "iopub.execute_input": "2023-08-22T06:59:07.939184Z", + "iopub.status.busy": "2023-08-22T06:59:07.938968Z", + "iopub.status.idle": "2023-08-22T06:59:07.941378Z", + "shell.execute_reply": "2023-08-22T06:59:07.941135Z" }, "lines_to_next_cell": 0 }, @@ -537,10 +537,10 @@ "id": "75bf1b1e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.804503Z", - "iopub.status.busy": "2023-08-21T03:36:04.804231Z", - "iopub.status.idle": "2023-08-21T03:36:04.810136Z", - "shell.execute_reply": "2023-08-21T03:36:04.809353Z" + "iopub.execute_input": "2023-08-22T06:59:07.943172Z", + "iopub.status.busy": "2023-08-22T06:59:07.942965Z", + "iopub.status.idle": "2023-08-22T06:59:07.945452Z", + "shell.execute_reply": "2023-08-22T06:59:07.945026Z" } }, "outputs": [ @@ -575,10 +575,10 @@ "id": "58292240", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.813981Z", - "iopub.status.busy": "2023-08-21T03:36:04.813417Z", - "iopub.status.idle": "2023-08-21T03:36:04.819511Z", - "shell.execute_reply": "2023-08-21T03:36:04.818936Z" + "iopub.execute_input": "2023-08-22T06:59:07.947238Z", + "iopub.status.busy": "2023-08-22T06:59:07.947112Z", + "iopub.status.idle": "2023-08-22T06:59:07.949367Z", + "shell.execute_reply": "2023-08-22T06:59:07.949033Z" }, "lines_to_next_cell": 0 }, @@ -615,10 +615,10 @@ "id": "fc5fff57", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.823519Z", - "iopub.status.busy": "2023-08-21T03:36:04.823222Z", - "iopub.status.idle": "2023-08-21T03:36:04.829861Z", - "shell.execute_reply": "2023-08-21T03:36:04.829223Z" + "iopub.execute_input": "2023-08-22T06:59:07.951095Z", + "iopub.status.busy": "2023-08-22T06:59:07.950962Z", + "iopub.status.idle": "2023-08-22T06:59:07.953323Z", + "shell.execute_reply": "2023-08-22T06:59:07.953058Z" }, "lines_to_next_cell": 2 }, @@ -654,10 +654,10 @@ "id": "762562a6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.833747Z", - "iopub.status.busy": "2023-08-21T03:36:04.833468Z", - "iopub.status.idle": "2023-08-21T03:36:04.838421Z", - "shell.execute_reply": "2023-08-21T03:36:04.837747Z" + "iopub.execute_input": "2023-08-22T06:59:07.955159Z", + "iopub.status.busy": "2023-08-22T06:59:07.955029Z", + "iopub.status.idle": "2023-08-22T06:59:07.957291Z", + "shell.execute_reply": "2023-08-22T06:59:07.956944Z" }, "lines_to_next_cell": 0 }, @@ -680,10 +680,10 @@ "id": "66d2b82a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.842127Z", - "iopub.status.busy": "2023-08-21T03:36:04.841891Z", - "iopub.status.idle": "2023-08-21T03:36:04.848885Z", - "shell.execute_reply": "2023-08-21T03:36:04.848125Z" + "iopub.execute_input": "2023-08-22T06:59:07.959022Z", + "iopub.status.busy": "2023-08-22T06:59:07.958921Z", + "iopub.status.idle": "2023-08-22T06:59:07.961144Z", + "shell.execute_reply": "2023-08-22T06:59:07.960798Z" }, "lines_to_next_cell": 2 }, @@ -718,10 +718,10 @@ "id": "89881402", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.853039Z", - "iopub.status.busy": "2023-08-21T03:36:04.852643Z", - "iopub.status.idle": "2023-08-21T03:36:04.859072Z", - "shell.execute_reply": "2023-08-21T03:36:04.858149Z" + "iopub.execute_input": "2023-08-22T06:59:07.963075Z", + "iopub.status.busy": "2023-08-22T06:59:07.962934Z", + "iopub.status.idle": "2023-08-22T06:59:07.965265Z", + "shell.execute_reply": "2023-08-22T06:59:07.964978Z" }, "lines_to_next_cell": 2 }, @@ -761,10 +761,10 @@ "id": "0572d3f6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.863011Z", - "iopub.status.busy": "2023-08-21T03:36:04.862610Z", - "iopub.status.idle": "2023-08-21T03:36:04.869722Z", - "shell.execute_reply": "2023-08-21T03:36:04.869078Z" + "iopub.execute_input": "2023-08-22T06:59:07.967468Z", + "iopub.status.busy": "2023-08-22T06:59:07.967139Z", + "iopub.status.idle": "2023-08-22T06:59:07.969644Z", + "shell.execute_reply": "2023-08-22T06:59:07.969386Z" }, "lines_to_next_cell": 0 }, @@ -799,10 +799,10 @@ "id": "33b10a6f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.874228Z", - "iopub.status.busy": "2023-08-21T03:36:04.873632Z", - "iopub.status.idle": "2023-08-21T03:36:04.879222Z", - "shell.execute_reply": "2023-08-21T03:36:04.878606Z" + "iopub.execute_input": "2023-08-22T06:59:07.971652Z", + "iopub.status.busy": "2023-08-22T06:59:07.971489Z", + "iopub.status.idle": "2023-08-22T06:59:07.974229Z", + "shell.execute_reply": "2023-08-22T06:59:07.973900Z" }, "lines_to_next_cell": 0 }, @@ -845,10 +845,10 @@ "id": "a32716db", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.882833Z", - "iopub.status.busy": "2023-08-21T03:36:04.882354Z", - "iopub.status.idle": "2023-08-21T03:36:04.887384Z", - "shell.execute_reply": "2023-08-21T03:36:04.886127Z" + "iopub.execute_input": "2023-08-22T06:59:07.976214Z", + "iopub.status.busy": "2023-08-22T06:59:07.976066Z", + "iopub.status.idle": "2023-08-22T06:59:07.978551Z", + "shell.execute_reply": "2023-08-22T06:59:07.978148Z" } }, "outputs": [ @@ -896,10 +896,10 @@ "id": "3db6e1cf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.890861Z", - "iopub.status.busy": "2023-08-21T03:36:04.890532Z", - "iopub.status.idle": "2023-08-21T03:36:04.894815Z", - "shell.execute_reply": "2023-08-21T03:36:04.894149Z" + "iopub.execute_input": "2023-08-22T06:59:07.980462Z", + "iopub.status.busy": "2023-08-22T06:59:07.980329Z", + "iopub.status.idle": "2023-08-22T06:59:07.982878Z", + "shell.execute_reply": "2023-08-22T06:59:07.982438Z" }, "lines_to_next_cell": 0 }, @@ -934,10 +934,10 @@ "id": "e15c753f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.898049Z", - "iopub.status.busy": "2023-08-21T03:36:04.897796Z", - "iopub.status.idle": "2023-08-21T03:36:04.902137Z", - "shell.execute_reply": "2023-08-21T03:36:04.901538Z" + "iopub.execute_input": "2023-08-22T06:59:07.984961Z", + "iopub.status.busy": "2023-08-22T06:59:07.984816Z", + "iopub.status.idle": "2023-08-22T06:59:07.987101Z", + "shell.execute_reply": "2023-08-22T06:59:07.986805Z" }, "lines_to_next_cell": 0 }, @@ -975,10 +975,10 @@ "id": "91c6e7d8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.905358Z", - "iopub.status.busy": "2023-08-21T03:36:04.905148Z", - "iopub.status.idle": "2023-08-21T03:36:04.910143Z", - "shell.execute_reply": "2023-08-21T03:36:04.909500Z" + "iopub.execute_input": "2023-08-22T06:59:07.989269Z", + "iopub.status.busy": "2023-08-22T06:59:07.988940Z", + "iopub.status.idle": "2023-08-22T06:59:07.991567Z", + "shell.execute_reply": "2023-08-22T06:59:07.991233Z" } }, "outputs": [ @@ -1033,10 +1033,10 @@ "id": "59d95dce", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:04.913411Z", - "iopub.status.busy": "2023-08-21T03:36:04.912985Z", - "iopub.status.idle": "2023-08-21T03:36:05.037046Z", - "shell.execute_reply": "2023-08-21T03:36:05.036755Z" + "iopub.execute_input": "2023-08-22T06:59:07.993423Z", + "iopub.status.busy": "2023-08-22T06:59:07.993299Z", + "iopub.status.idle": "2023-08-22T06:59:08.133462Z", + "shell.execute_reply": "2023-08-22T06:59:08.132910Z" }, "lines_to_next_cell": 2 }, @@ -1073,10 +1073,10 @@ "id": "a6fde9af", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.038645Z", - "iopub.status.busy": "2023-08-21T03:36:05.038536Z", - "iopub.status.idle": "2023-08-21T03:36:05.040823Z", - "shell.execute_reply": "2023-08-21T03:36:05.040589Z" + "iopub.execute_input": "2023-08-22T06:59:08.135655Z", + "iopub.status.busy": "2023-08-22T06:59:08.135507Z", + "iopub.status.idle": "2023-08-22T06:59:08.138481Z", + "shell.execute_reply": "2023-08-22T06:59:08.138180Z" } }, "outputs": [ @@ -1117,10 +1117,10 @@ "id": "fadb6b45", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.042203Z", - "iopub.status.busy": "2023-08-21T03:36:05.042112Z", - "iopub.status.idle": "2023-08-21T03:36:05.044185Z", - "shell.execute_reply": "2023-08-21T03:36:05.043940Z" + "iopub.execute_input": "2023-08-22T06:59:08.140173Z", + "iopub.status.busy": "2023-08-22T06:59:08.140051Z", + "iopub.status.idle": "2023-08-22T06:59:08.142777Z", + "shell.execute_reply": "2023-08-22T06:59:08.142404Z" } }, "outputs": [ @@ -1154,10 +1154,10 @@ "id": "fda3134b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.045709Z", - "iopub.status.busy": "2023-08-21T03:36:05.045601Z", - "iopub.status.idle": "2023-08-21T03:36:05.047665Z", - "shell.execute_reply": "2023-08-21T03:36:05.047412Z" + "iopub.execute_input": "2023-08-22T06:59:08.144782Z", + "iopub.status.busy": "2023-08-22T06:59:08.144640Z", + "iopub.status.idle": "2023-08-22T06:59:08.147297Z", + "shell.execute_reply": "2023-08-22T06:59:08.146996Z" } }, "outputs": [ @@ -1190,10 +1190,10 @@ "id": "52eb335b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.049290Z", - "iopub.status.busy": "2023-08-21T03:36:05.049191Z", - "iopub.status.idle": "2023-08-21T03:36:05.051249Z", - "shell.execute_reply": "2023-08-21T03:36:05.051004Z" + "iopub.execute_input": "2023-08-22T06:59:08.148995Z", + "iopub.status.busy": "2023-08-22T06:59:08.148870Z", + "iopub.status.idle": "2023-08-22T06:59:08.151571Z", + "shell.execute_reply": "2023-08-22T06:59:08.151251Z" }, "lines_to_next_cell": 2 }, @@ -1237,26 +1237,26 @@ "id": "ac5e9d29", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.052622Z", - "iopub.status.busy": "2023-08-21T03:36:05.052529Z", - "iopub.status.idle": "2023-08-21T03:36:05.054818Z", - "shell.execute_reply": "2023-08-21T03:36:05.054569Z" + "iopub.execute_input": "2023-08-22T06:59:08.154113Z", + "iopub.status.busy": "2023-08-22T06:59:08.153958Z", + "iopub.status.idle": "2023-08-22T06:59:08.157534Z", + "shell.execute_reply": "2023-08-22T06:59:08.156973Z" } }, "outputs": [ { "data": { "text/plain": [ - "array([-0.97992307, 0.29561095, 0.60481929, -0.20482365, -1.01517527,\n", - " 2.76594674, -0.65748447, 1.27396181, -1.01573869, 1.37373688,\n", - " 0.93524901, -2.41971622, -0.58080017, 0.13777341, 1.35936356,\n", - " 0.61747629, 0.82550921, 0.7943598 , 1.0905082 , 1.80820045,\n", - " -1.31320321, 2.0651966 , -0.78632522, -2.01068042, -1.36562571,\n", - " 1.43466837, -0.16848093, -1.57211786, 0.49888498, -1.86050966,\n", - " 1.08743609, 0.53059599, 0.02172848, -0.41808062, 1.88343414,\n", - " 0.09112977, 1.23489568, 0.53207714, -1.62670383, 1.29859234,\n", - " 0.30311344, 1.01143392, -1.64596169, 1.58876421, -1.85189683,\n", - " -0.53929878, -2.19895144, -0.36691225, 1.03621761, 0.25278481])" + "array([-0.83511556, 0.43461482, -1.3810022 , -0.64162363, -0.86270682,\n", + " 0.6660104 , 0.17543353, 0.68220139, -0.20392851, -1.47534629,\n", + " 0.18438201, 1.50157883, 0.47473968, -1.33062844, 1.57614184,\n", + " -0.25596784, 0.66848396, -1.5410464 , 0.25298297, -0.79118181,\n", + " -0.49399731, -1.45139182, 0.71261617, 1.19862796, 0.52772362,\n", + " 0.57343239, -0.01577204, 2.56032683, -0.18936979, -0.09651695,\n", + " -1.74331796, 0.11390389, 0.27595492, 1.2606086 , 0.49282705,\n", + " 0.60603827, 0.24699795, 0.28636264, 0.54683924, 0.45133321,\n", + " 0.92563958, 1.20847512, 0.40993092, 0.01951345, 0.27271415,\n", + " 0.94231124, 0.47471813, 2.12851232, 0.128139 , -0.56681371])" ] }, "execution_count": 28, @@ -1283,10 +1283,10 @@ "id": "55fa905e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.056219Z", - "iopub.status.busy": "2023-08-21T03:36:05.056124Z", - "iopub.status.idle": "2023-08-21T03:36:05.057790Z", - "shell.execute_reply": "2023-08-21T03:36:05.057543Z" + "iopub.execute_input": "2023-08-22T06:59:08.159589Z", + "iopub.status.busy": "2023-08-22T06:59:08.159437Z", + "iopub.status.idle": "2023-08-22T06:59:08.161722Z", + "shell.execute_reply": "2023-08-22T06:59:08.161369Z" }, "lines_to_next_cell": 0 }, @@ -1310,18 +1310,18 @@ "id": "fde0dc19", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.059163Z", - "iopub.status.busy": "2023-08-21T03:36:05.059091Z", - "iopub.status.idle": "2023-08-21T03:36:05.061351Z", - "shell.execute_reply": "2023-08-21T03:36:05.061105Z" + "iopub.execute_input": "2023-08-22T06:59:08.164153Z", + "iopub.status.busy": "2023-08-22T06:59:08.163979Z", + "iopub.status.idle": "2023-08-22T06:59:08.168094Z", + "shell.execute_reply": "2023-08-22T06:59:08.167676Z" } }, "outputs": [ { "data": { "text/plain": [ - "array([[1. , 0.66045794],\n", - " [0.66045794, 1. ]])" + "array([[1. , 0.65985439],\n", + " [0.65985439, 1. ]])" ] }, "execution_count": 30, @@ -1350,10 +1350,10 @@ "id": "5099cf54", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.062721Z", - "iopub.status.busy": "2023-08-21T03:36:05.062630Z", - "iopub.status.idle": "2023-08-21T03:36:05.064539Z", - "shell.execute_reply": "2023-08-21T03:36:05.064300Z" + "iopub.execute_input": "2023-08-22T06:59:08.169980Z", + "iopub.status.busy": "2023-08-22T06:59:08.169865Z", + "iopub.status.idle": "2023-08-22T06:59:08.173468Z", + "shell.execute_reply": "2023-08-22T06:59:08.172857Z" }, "lines_to_next_cell": 0 }, @@ -1362,8 +1362,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "[-9.63514647 -0.12742473]\n", - "[0.85490033 0.05488893]\n" + "[ 6.33922704 -0.66068102]\n", + "[-6.96104352 18.61644142]\n" ] } ], @@ -1401,10 +1401,10 @@ "id": "9d8074e5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.065999Z", - "iopub.status.busy": "2023-08-21T03:36:05.065912Z", - "iopub.status.idle": "2023-08-21T03:36:05.068039Z", - "shell.execute_reply": "2023-08-21T03:36:05.067820Z" + "iopub.execute_input": "2023-08-22T06:59:08.175381Z", + "iopub.status.busy": "2023-08-22T06:59:08.175239Z", + "iopub.status.idle": "2023-08-22T06:59:08.177926Z", + "shell.execute_reply": "2023-08-22T06:59:08.177603Z" } }, "outputs": [ @@ -1447,10 +1447,10 @@ "id": "e98472df", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.069438Z", - "iopub.status.busy": "2023-08-21T03:36:05.069347Z", - "iopub.status.idle": "2023-08-21T03:36:05.071564Z", - "shell.execute_reply": "2023-08-21T03:36:05.071324Z" + "iopub.execute_input": "2023-08-22T06:59:08.179784Z", + "iopub.status.busy": "2023-08-22T06:59:08.179647Z", + "iopub.status.idle": "2023-08-22T06:59:08.182540Z", + "shell.execute_reply": "2023-08-22T06:59:08.182002Z" }, "lines_to_next_cell": 0 }, @@ -1486,10 +1486,10 @@ "id": "8c2784fd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.072967Z", - "iopub.status.busy": "2023-08-21T03:36:05.072873Z", - "iopub.status.idle": "2023-08-21T03:36:05.075053Z", - "shell.execute_reply": "2023-08-21T03:36:05.074833Z" + "iopub.execute_input": "2023-08-22T06:59:08.184240Z", + "iopub.status.busy": "2023-08-22T06:59:08.184117Z", + "iopub.status.idle": "2023-08-22T06:59:08.186691Z", + "shell.execute_reply": "2023-08-22T06:59:08.186367Z" }, "lines_to_next_cell": 2 }, @@ -1524,10 +1524,10 @@ "id": "7e7205f2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.076473Z", - "iopub.status.busy": "2023-08-21T03:36:05.076373Z", - "iopub.status.idle": "2023-08-21T03:36:05.078474Z", - "shell.execute_reply": "2023-08-21T03:36:05.078224Z" + "iopub.execute_input": "2023-08-22T06:59:08.188421Z", + "iopub.status.busy": "2023-08-22T06:59:08.188291Z", + "iopub.status.idle": "2023-08-22T06:59:08.191242Z", + "shell.execute_reply": "2023-08-22T06:59:08.190935Z" } }, "outputs": [ @@ -1561,10 +1561,10 @@ "id": "fce06849", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.079856Z", - "iopub.status.busy": "2023-08-21T03:36:05.079755Z", - "iopub.status.idle": "2023-08-21T03:36:05.081961Z", - "shell.execute_reply": "2023-08-21T03:36:05.081709Z" + "iopub.execute_input": "2023-08-22T06:59:08.192889Z", + "iopub.status.busy": "2023-08-22T06:59:08.192762Z", + "iopub.status.idle": "2023-08-22T06:59:08.195517Z", + "shell.execute_reply": "2023-08-22T06:59:08.195194Z" } }, "outputs": [ @@ -1607,10 +1607,10 @@ "id": "1403ff7a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.083361Z", - "iopub.status.busy": "2023-08-21T03:36:05.083273Z", - "iopub.status.idle": "2023-08-21T03:36:05.085366Z", - "shell.execute_reply": "2023-08-21T03:36:05.085112Z" + "iopub.execute_input": "2023-08-22T06:59:08.197212Z", + "iopub.status.busy": "2023-08-22T06:59:08.197063Z", + "iopub.status.idle": "2023-08-22T06:59:08.199463Z", + "shell.execute_reply": "2023-08-22T06:59:08.199082Z" } }, "outputs": [ @@ -1643,10 +1643,10 @@ "id": "7e9255ba", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.086730Z", - "iopub.status.busy": "2023-08-21T03:36:05.086636Z", - "iopub.status.idle": "2023-08-21T03:36:05.088698Z", - "shell.execute_reply": "2023-08-21T03:36:05.088470Z" + "iopub.execute_input": "2023-08-22T06:59:08.201135Z", + "iopub.status.busy": "2023-08-22T06:59:08.201013Z", + "iopub.status.idle": "2023-08-22T06:59:08.203278Z", + "shell.execute_reply": "2023-08-22T06:59:08.202984Z" }, "lines_to_next_cell": 0 }, @@ -1713,10 +1713,10 @@ "id": "8236e5f7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.090105Z", - "iopub.status.busy": "2023-08-21T03:36:05.090015Z", - "iopub.status.idle": "2023-08-21T03:36:05.390499Z", - "shell.execute_reply": "2023-08-21T03:36:05.390143Z" + "iopub.execute_input": "2023-08-22T06:59:08.205399Z", + "iopub.status.busy": "2023-08-22T06:59:08.205262Z", + "iopub.status.idle": "2023-08-22T06:59:09.267032Z", + "shell.execute_reply": "2023-08-22T06:59:09.266627Z" } }, "outputs": [ @@ -1755,10 +1755,10 @@ "id": "ddc9ed4f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.392242Z", - "iopub.status.busy": "2023-08-21T03:36:05.392127Z", - "iopub.status.idle": "2023-08-21T03:36:05.464507Z", - "shell.execute_reply": "2023-08-21T03:36:05.464208Z" + "iopub.execute_input": "2023-08-22T06:59:09.269192Z", + "iopub.status.busy": "2023-08-22T06:59:09.269015Z", + "iopub.status.idle": "2023-08-22T06:59:09.336385Z", + "shell.execute_reply": "2023-08-22T06:59:09.335994Z" } }, "outputs": [ @@ -1793,10 +1793,10 @@ "id": "c64ed600", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.466274Z", - "iopub.status.busy": "2023-08-21T03:36:05.466157Z", - "iopub.status.idle": "2023-08-21T03:36:05.540801Z", - "shell.execute_reply": "2023-08-21T03:36:05.540543Z" + "iopub.execute_input": "2023-08-22T06:59:09.338601Z", + "iopub.status.busy": "2023-08-22T06:59:09.338466Z", + "iopub.status.idle": "2023-08-22T06:59:09.408187Z", + "shell.execute_reply": "2023-08-22T06:59:09.407850Z" }, "lines_to_next_cell": 0 }, @@ -1841,10 +1841,10 @@ "id": "bc6245e2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.542497Z", - "iopub.status.busy": "2023-08-21T03:36:05.542378Z", - "iopub.status.idle": "2023-08-21T03:36:05.621061Z", - "shell.execute_reply": "2023-08-21T03:36:05.620765Z" + "iopub.execute_input": "2023-08-22T06:59:09.410036Z", + "iopub.status.busy": "2023-08-22T06:59:09.409914Z", + "iopub.status.idle": "2023-08-22T06:59:09.481803Z", + "shell.execute_reply": "2023-08-22T06:59:09.481516Z" } }, "outputs": [ @@ -1881,10 +1881,10 @@ "id": "2454807b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.622738Z", - "iopub.status.busy": "2023-08-21T03:36:05.622624Z", - "iopub.status.idle": "2023-08-21T03:36:05.700853Z", - "shell.execute_reply": "2023-08-21T03:36:05.700564Z" + "iopub.execute_input": "2023-08-22T06:59:09.483769Z", + "iopub.status.busy": "2023-08-22T06:59:09.483410Z", + "iopub.status.idle": "2023-08-22T06:59:09.583871Z", + "shell.execute_reply": "2023-08-22T06:59:09.583567Z" }, "lines_to_next_cell": 0 }, @@ -1892,7 +1892,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 43, @@ -1944,10 +1944,10 @@ "id": "1e18a793", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.702667Z", - "iopub.status.busy": "2023-08-21T03:36:05.702545Z", - "iopub.status.idle": "2023-08-21T03:36:05.797850Z", - "shell.execute_reply": "2023-08-21T03:36:05.797545Z" + "iopub.execute_input": "2023-08-22T06:59:09.585676Z", + "iopub.status.busy": "2023-08-22T06:59:09.585555Z", + "iopub.status.idle": "2023-08-22T06:59:09.674249Z", + "shell.execute_reply": "2023-08-22T06:59:09.673902Z" } }, "outputs": [ @@ -1985,10 +1985,10 @@ "id": "aec3f009", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.799658Z", - "iopub.status.busy": "2023-08-21T03:36:05.799529Z", - "iopub.status.idle": "2023-08-21T03:36:05.861021Z", - "shell.execute_reply": "2023-08-21T03:36:05.860749Z" + "iopub.execute_input": "2023-08-22T06:59:09.676005Z", + "iopub.status.busy": "2023-08-22T06:59:09.675879Z", + "iopub.status.idle": "2023-08-22T06:59:09.733152Z", + "shell.execute_reply": "2023-08-22T06:59:09.732799Z" }, "lines_to_next_cell": 0 }, @@ -2039,10 +2039,10 @@ "id": "2cbc7fd4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:05.862740Z", - "iopub.status.busy": "2023-08-21T03:36:05.862621Z", - "iopub.status.idle": "2023-08-21T03:36:06.143924Z", - "shell.execute_reply": "2023-08-21T03:36:06.143646Z" + "iopub.execute_input": "2023-08-22T06:59:09.734976Z", + "iopub.status.busy": "2023-08-22T06:59:09.734855Z", + "iopub.status.idle": "2023-08-22T06:59:09.987982Z", + "shell.execute_reply": "2023-08-22T06:59:09.987518Z" }, "lines_to_next_cell": 0 }, @@ -2079,10 +2079,10 @@ "id": "702f80d9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:06.145683Z", - "iopub.status.busy": "2023-08-21T03:36:06.145574Z", - "iopub.status.idle": "2023-08-21T03:36:06.326301Z", - "shell.execute_reply": "2023-08-21T03:36:06.326007Z" + "iopub.execute_input": "2023-08-22T06:59:09.989943Z", + "iopub.status.busy": "2023-08-22T06:59:09.989799Z", + "iopub.status.idle": "2023-08-22T06:59:10.164367Z", + "shell.execute_reply": "2023-08-22T06:59:10.164050Z" }, "lines_to_next_cell": 0 }, @@ -2132,10 +2132,10 @@ "id": "5493d229", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:06.327958Z", - "iopub.status.busy": "2023-08-21T03:36:06.327847Z", - "iopub.status.idle": "2023-08-21T03:36:07.432805Z", - "shell.execute_reply": "2023-08-21T03:36:07.432429Z" + "iopub.execute_input": "2023-08-22T06:59:10.166485Z", + "iopub.status.busy": "2023-08-22T06:59:10.166339Z", + "iopub.status.idle": "2023-08-22T06:59:11.473366Z", + "shell.execute_reply": "2023-08-22T06:59:11.473053Z" }, "lines_to_next_cell": 2 }, @@ -2159,10 +2159,10 @@ "id": "bd07af12", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:07.434785Z", - "iopub.status.busy": "2023-08-21T03:36:07.434614Z", - "iopub.status.idle": "2023-08-21T03:36:07.663475Z", - "shell.execute_reply": "2023-08-21T03:36:07.663165Z" + "iopub.execute_input": "2023-08-22T06:59:11.475355Z", + "iopub.status.busy": "2023-08-22T06:59:11.475181Z", + "iopub.status.idle": "2023-08-22T06:59:11.696662Z", + "shell.execute_reply": "2023-08-22T06:59:11.696345Z" } }, "outputs": [ @@ -2209,10 +2209,10 @@ "id": "01019508", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:07.665255Z", - "iopub.status.busy": "2023-08-21T03:36:07.665128Z", - "iopub.status.idle": "2023-08-21T03:36:07.766569Z", - "shell.execute_reply": "2023-08-21T03:36:07.766244Z" + "iopub.execute_input": "2023-08-22T06:59:11.698588Z", + "iopub.status.busy": "2023-08-22T06:59:11.698446Z", + "iopub.status.idle": "2023-08-22T06:59:11.986555Z", + "shell.execute_reply": "2023-08-22T06:59:11.986111Z" }, "lines_to_next_cell": 0 }, @@ -2250,10 +2250,10 @@ "id": "7d08992f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:07.768244Z", - "iopub.status.busy": "2023-08-21T03:36:07.768130Z", - "iopub.status.idle": "2023-08-21T03:36:07.893027Z", - "shell.execute_reply": "2023-08-21T03:36:07.892660Z" + "iopub.execute_input": "2023-08-22T06:59:11.988767Z", + "iopub.status.busy": "2023-08-22T06:59:11.988614Z", + "iopub.status.idle": "2023-08-22T06:59:12.104022Z", + "shell.execute_reply": "2023-08-22T06:59:12.103708Z" }, "lines_to_next_cell": 0 }, @@ -2296,10 +2296,10 @@ "id": "1f89d704", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:07.894802Z", - "iopub.status.busy": "2023-08-21T03:36:07.894695Z", - "iopub.status.idle": "2023-08-21T03:36:07.995202Z", - "shell.execute_reply": "2023-08-21T03:36:07.994863Z" + "iopub.execute_input": "2023-08-22T06:59:12.105969Z", + "iopub.status.busy": "2023-08-22T06:59:12.105871Z", + "iopub.status.idle": "2023-08-22T06:59:12.198374Z", + "shell.execute_reply": "2023-08-22T06:59:12.197945Z" }, "lines_to_next_cell": 2 }, @@ -2344,10 +2344,10 @@ "id": "cd971131", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:07.996961Z", - "iopub.status.busy": "2023-08-21T03:36:07.996836Z", - "iopub.status.idle": "2023-08-21T03:36:07.999447Z", - "shell.execute_reply": "2023-08-21T03:36:07.999154Z" + "iopub.execute_input": "2023-08-22T06:59:12.200827Z", + "iopub.status.busy": "2023-08-22T06:59:12.200655Z", + "iopub.status.idle": "2023-08-22T06:59:12.203494Z", + "shell.execute_reply": "2023-08-22T06:59:12.203195Z" }, "lines_to_next_cell": 2 }, @@ -2384,10 +2384,10 @@ "id": "aa630d16", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.001028Z", - "iopub.status.busy": "2023-08-21T03:36:08.000925Z", - "iopub.status.idle": "2023-08-21T03:36:08.003185Z", - "shell.execute_reply": "2023-08-21T03:36:08.002908Z" + "iopub.execute_input": "2023-08-22T06:59:12.205484Z", + "iopub.status.busy": "2023-08-22T06:59:12.205351Z", + "iopub.status.idle": "2023-08-22T06:59:12.207885Z", + "shell.execute_reply": "2023-08-22T06:59:12.207564Z" } }, "outputs": [ @@ -2425,10 +2425,10 @@ "id": "89955ee2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.004703Z", - "iopub.status.busy": "2023-08-21T03:36:08.004594Z", - "iopub.status.idle": "2023-08-21T03:36:08.006692Z", - "shell.execute_reply": "2023-08-21T03:36:08.006429Z" + "iopub.execute_input": "2023-08-22T06:59:12.209574Z", + "iopub.status.busy": "2023-08-22T06:59:12.209454Z", + "iopub.status.idle": "2023-08-22T06:59:12.212189Z", + "shell.execute_reply": "2023-08-22T06:59:12.211670Z" }, "lines_to_next_cell": 0 }, @@ -2463,10 +2463,10 @@ "id": "517f592d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.008158Z", - "iopub.status.busy": "2023-08-21T03:36:08.008062Z", - "iopub.status.idle": "2023-08-21T03:36:08.010083Z", - "shell.execute_reply": "2023-08-21T03:36:08.009819Z" + "iopub.execute_input": "2023-08-22T06:59:12.214090Z", + "iopub.status.busy": "2023-08-22T06:59:12.213954Z", + "iopub.status.idle": "2023-08-22T06:59:12.216634Z", + "shell.execute_reply": "2023-08-22T06:59:12.216229Z" } }, "outputs": [ @@ -2530,10 +2530,10 @@ "id": "35927abd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.011518Z", - "iopub.status.busy": "2023-08-21T03:36:08.011425Z", - "iopub.status.idle": "2023-08-21T03:36:08.013558Z", - "shell.execute_reply": "2023-08-21T03:36:08.013317Z" + "iopub.execute_input": "2023-08-22T06:59:12.218701Z", + "iopub.status.busy": "2023-08-22T06:59:12.218551Z", + "iopub.status.idle": "2023-08-22T06:59:12.221779Z", + "shell.execute_reply": "2023-08-22T06:59:12.221078Z" } }, "outputs": [ @@ -2571,10 +2571,10 @@ "id": "78ee7f5b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.014962Z", - "iopub.status.busy": "2023-08-21T03:36:08.014871Z", - "iopub.status.idle": "2023-08-21T03:36:08.016938Z", - "shell.execute_reply": "2023-08-21T03:36:08.016689Z" + "iopub.execute_input": "2023-08-22T06:59:12.223849Z", + "iopub.status.busy": "2023-08-22T06:59:12.223730Z", + "iopub.status.idle": "2023-08-22T06:59:12.226375Z", + "shell.execute_reply": "2023-08-22T06:59:12.226073Z" } }, "outputs": [ @@ -2612,10 +2612,10 @@ "id": "16212696", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.018506Z", - "iopub.status.busy": "2023-08-21T03:36:08.018407Z", - "iopub.status.idle": "2023-08-21T03:36:08.020572Z", - "shell.execute_reply": "2023-08-21T03:36:08.020301Z" + "iopub.execute_input": "2023-08-22T06:59:12.228118Z", + "iopub.status.busy": "2023-08-22T06:59:12.227993Z", + "iopub.status.idle": "2023-08-22T06:59:12.230254Z", + "shell.execute_reply": "2023-08-22T06:59:12.229993Z" } }, "outputs": [ @@ -2651,10 +2651,10 @@ "id": "d5f473d2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.022048Z", - "iopub.status.busy": "2023-08-21T03:36:08.021947Z", - "iopub.status.idle": "2023-08-21T03:36:08.024301Z", - "shell.execute_reply": "2023-08-21T03:36:08.024006Z" + "iopub.execute_input": "2023-08-22T06:59:12.231967Z", + "iopub.status.busy": "2023-08-22T06:59:12.231858Z", + "iopub.status.idle": "2023-08-22T06:59:12.234317Z", + "shell.execute_reply": "2023-08-22T06:59:12.234032Z" } }, "outputs": [ @@ -2692,10 +2692,10 @@ "id": "c89646d6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.025864Z", - "iopub.status.busy": "2023-08-21T03:36:08.025745Z", - "iopub.status.idle": "2023-08-21T03:36:08.027990Z", - "shell.execute_reply": "2023-08-21T03:36:08.027692Z" + "iopub.execute_input": "2023-08-22T06:59:12.236331Z", + "iopub.status.busy": "2023-08-22T06:59:12.236194Z", + "iopub.status.idle": "2023-08-22T06:59:12.238788Z", + "shell.execute_reply": "2023-08-22T06:59:12.238448Z" } }, "outputs": [ @@ -2728,10 +2728,10 @@ "id": "87f6b4f2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.029541Z", - "iopub.status.busy": "2023-08-21T03:36:08.029439Z", - "iopub.status.idle": "2023-08-21T03:36:08.031650Z", - "shell.execute_reply": "2023-08-21T03:36:08.031378Z" + "iopub.execute_input": "2023-08-22T06:59:12.240562Z", + "iopub.status.busy": "2023-08-22T06:59:12.240434Z", + "iopub.status.idle": "2023-08-22T06:59:12.242956Z", + "shell.execute_reply": "2023-08-22T06:59:12.242696Z" } }, "outputs": [ @@ -2764,10 +2764,10 @@ "id": "5da5bda8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.033127Z", - "iopub.status.busy": "2023-08-21T03:36:08.033016Z", - "iopub.status.idle": "2023-08-21T03:36:08.056275Z", - "shell.execute_reply": "2023-08-21T03:36:08.056014Z" + "iopub.execute_input": "2023-08-22T06:59:12.244576Z", + "iopub.status.busy": "2023-08-22T06:59:12.244457Z", + "iopub.status.idle": "2023-08-22T06:59:12.267725Z", + "shell.execute_reply": "2023-08-22T06:59:12.267329Z" } }, "outputs": [ @@ -2803,10 +2803,10 @@ "id": "ac48a95b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.057926Z", - "iopub.status.busy": "2023-08-21T03:36:08.057815Z", - "iopub.status.idle": "2023-08-21T03:36:08.060231Z", - "shell.execute_reply": "2023-08-21T03:36:08.059980Z" + "iopub.execute_input": "2023-08-22T06:59:12.269754Z", + "iopub.status.busy": "2023-08-22T06:59:12.269614Z", + "iopub.status.idle": "2023-08-22T06:59:12.272265Z", + "shell.execute_reply": "2023-08-22T06:59:12.271962Z" }, "lines_to_next_cell": 0 }, @@ -2852,10 +2852,10 @@ "id": "ee195cc4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.061798Z", - "iopub.status.busy": "2023-08-21T03:36:08.061686Z", - "iopub.status.idle": "2023-08-21T03:36:08.063979Z", - "shell.execute_reply": "2023-08-21T03:36:08.063715Z" + "iopub.execute_input": "2023-08-22T06:59:12.273998Z", + "iopub.status.busy": "2023-08-22T06:59:12.273857Z", + "iopub.status.idle": "2023-08-22T06:59:12.276565Z", + "shell.execute_reply": "2023-08-22T06:59:12.276235Z" }, "lines_to_next_cell": 2 }, @@ -2895,10 +2895,10 @@ "id": "48917bb5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.067067Z", - "iopub.status.busy": "2023-08-21T03:36:08.066955Z", - "iopub.status.idle": "2023-08-21T03:36:08.069279Z", - "shell.execute_reply": "2023-08-21T03:36:08.068966Z" + "iopub.execute_input": "2023-08-22T06:59:12.278649Z", + "iopub.status.busy": "2023-08-22T06:59:12.278494Z", + "iopub.status.idle": "2023-08-22T06:59:12.281280Z", + "shell.execute_reply": "2023-08-22T06:59:12.280843Z" }, "lines_to_next_cell": 0 }, @@ -2965,10 +2965,10 @@ "id": "5d4caf22", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.070903Z", - "iopub.status.busy": "2023-08-21T03:36:08.070799Z", - "iopub.status.idle": "2023-08-21T03:36:08.072959Z", - "shell.execute_reply": "2023-08-21T03:36:08.072701Z" + "iopub.execute_input": "2023-08-22T06:59:12.282968Z", + "iopub.status.busy": "2023-08-22T06:59:12.282854Z", + "iopub.status.idle": "2023-08-22T06:59:12.285234Z", + "shell.execute_reply": "2023-08-22T06:59:12.284961Z" }, "lines_to_next_cell": 0 }, @@ -3003,10 +3003,10 @@ "id": "348820e3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.074422Z", - "iopub.status.busy": "2023-08-21T03:36:08.074322Z", - "iopub.status.idle": "2023-08-21T03:36:08.076398Z", - "shell.execute_reply": "2023-08-21T03:36:08.076106Z" + "iopub.execute_input": "2023-08-22T06:59:12.287427Z", + "iopub.status.busy": "2023-08-22T06:59:12.287184Z", + "iopub.status.idle": "2023-08-22T06:59:12.289915Z", + "shell.execute_reply": "2023-08-22T06:59:12.289589Z" } }, "outputs": [ @@ -3042,10 +3042,10 @@ "id": "4aafe45b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.077952Z", - "iopub.status.busy": "2023-08-21T03:36:08.077853Z", - "iopub.status.idle": "2023-08-21T03:36:08.080163Z", - "shell.execute_reply": "2023-08-21T03:36:08.079901Z" + "iopub.execute_input": "2023-08-22T06:59:12.291767Z", + "iopub.status.busy": "2023-08-22T06:59:12.291634Z", + "iopub.status.idle": "2023-08-22T06:59:12.294302Z", + "shell.execute_reply": "2023-08-22T06:59:12.293967Z" } }, "outputs": [ @@ -3088,10 +3088,10 @@ "id": "1be6a588", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.081637Z", - "iopub.status.busy": "2023-08-21T03:36:08.081537Z", - "iopub.status.idle": "2023-08-21T03:36:08.083796Z", - "shell.execute_reply": "2023-08-21T03:36:08.083505Z" + "iopub.execute_input": "2023-08-22T06:59:12.296189Z", + "iopub.status.busy": "2023-08-22T06:59:12.296052Z", + "iopub.status.idle": "2023-08-22T06:59:12.298784Z", + "shell.execute_reply": "2023-08-22T06:59:12.298383Z" } }, "outputs": [ @@ -3127,10 +3127,10 @@ "id": "e83da57b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.085319Z", - "iopub.status.busy": "2023-08-21T03:36:08.085216Z", - "iopub.status.idle": "2023-08-21T03:36:08.087359Z", - "shell.execute_reply": "2023-08-21T03:36:08.087095Z" + "iopub.execute_input": "2023-08-22T06:59:12.300802Z", + "iopub.status.busy": "2023-08-22T06:59:12.300663Z", + "iopub.status.idle": "2023-08-22T06:59:12.303240Z", + "shell.execute_reply": "2023-08-22T06:59:12.302865Z" } }, "outputs": [ @@ -3174,10 +3174,10 @@ "id": "09675294", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.088904Z", - "iopub.status.busy": "2023-08-21T03:36:08.088804Z", - "iopub.status.idle": "2023-08-21T03:36:08.091266Z", - "shell.execute_reply": "2023-08-21T03:36:08.090985Z" + "iopub.execute_input": "2023-08-22T06:59:12.305143Z", + "iopub.status.busy": "2023-08-22T06:59:12.305025Z", + "iopub.status.idle": "2023-08-22T06:59:12.307529Z", + "shell.execute_reply": "2023-08-22T06:59:12.307219Z" } }, "outputs": [ @@ -3214,10 +3214,10 @@ "id": "a85614e4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.092757Z", - "iopub.status.busy": "2023-08-21T03:36:08.092664Z", - "iopub.status.idle": "2023-08-21T03:36:08.094873Z", - "shell.execute_reply": "2023-08-21T03:36:08.094581Z" + "iopub.execute_input": "2023-08-22T06:59:12.309554Z", + "iopub.status.busy": "2023-08-22T06:59:12.309418Z", + "iopub.status.idle": "2023-08-22T06:59:12.311737Z", + "shell.execute_reply": "2023-08-22T06:59:12.311441Z" }, "lines_to_next_cell": 0 }, @@ -3306,10 +3306,10 @@ "id": "ff81e644", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.096546Z", - "iopub.status.busy": "2023-08-21T03:36:08.096449Z", - "iopub.status.idle": "2023-08-21T03:36:08.317557Z", - "shell.execute_reply": "2023-08-21T03:36:08.317278Z" + "iopub.execute_input": "2023-08-22T06:59:12.313549Z", + "iopub.status.busy": "2023-08-22T06:59:12.313428Z", + "iopub.status.idle": "2023-08-22T06:59:14.571524Z", + "shell.execute_reply": "2023-08-22T06:59:14.571235Z" } }, "outputs": [ @@ -3538,10 +3538,10 @@ "id": "5b45aa7f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.319194Z", - "iopub.status.busy": "2023-08-21T03:36:08.319082Z", - "iopub.status.idle": "2023-08-21T03:36:08.322312Z", - "shell.execute_reply": "2023-08-21T03:36:08.322063Z" + "iopub.execute_input": "2023-08-22T06:59:14.573445Z", + "iopub.status.busy": "2023-08-22T06:59:14.573227Z", + "iopub.status.idle": "2023-08-22T06:59:14.576905Z", + "shell.execute_reply": "2023-08-22T06:59:14.576624Z" }, "lines_to_next_cell": 0 }, @@ -3575,10 +3575,10 @@ "id": "413f626a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.323776Z", - "iopub.status.busy": "2023-08-21T03:36:08.323686Z", - "iopub.status.idle": "2023-08-21T03:36:08.326230Z", - "shell.execute_reply": "2023-08-21T03:36:08.325989Z" + "iopub.execute_input": "2023-08-22T06:59:14.578771Z", + "iopub.status.busy": "2023-08-22T06:59:14.578606Z", + "iopub.status.idle": "2023-08-22T06:59:14.581727Z", + "shell.execute_reply": "2023-08-22T06:59:14.581462Z" }, "lines_to_next_cell": 0 }, @@ -3626,10 +3626,10 @@ "id": "57b86346", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.327630Z", - "iopub.status.busy": "2023-08-21T03:36:08.327527Z", - "iopub.status.idle": "2023-08-21T03:36:08.329871Z", - "shell.execute_reply": "2023-08-21T03:36:08.329620Z" + "iopub.execute_input": "2023-08-22T06:59:14.583287Z", + "iopub.status.busy": "2023-08-22T06:59:14.583182Z", + "iopub.status.idle": "2023-08-22T06:59:14.585660Z", + "shell.execute_reply": "2023-08-22T06:59:14.585401Z" }, "lines_to_next_cell": 0 }, @@ -3687,10 +3687,10 @@ "id": "a9698b26", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.331328Z", - "iopub.status.busy": "2023-08-21T03:36:08.331230Z", - "iopub.status.idle": "2023-08-21T03:36:08.334947Z", - "shell.execute_reply": "2023-08-21T03:36:08.334715Z" + "iopub.execute_input": "2023-08-22T06:59:14.587247Z", + "iopub.status.busy": "2023-08-22T06:59:14.587134Z", + "iopub.status.idle": "2023-08-22T06:59:14.591564Z", + "shell.execute_reply": "2023-08-22T06:59:14.591275Z" }, "lines_to_next_cell": 2 }, @@ -3728,10 +3728,10 @@ "id": "4877cb2c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.336400Z", - "iopub.status.busy": "2023-08-21T03:36:08.336322Z", - "iopub.status.idle": "2023-08-21T03:36:08.338340Z", - "shell.execute_reply": "2023-08-21T03:36:08.338101Z" + "iopub.execute_input": "2023-08-22T06:59:14.593387Z", + "iopub.status.busy": "2023-08-22T06:59:14.593233Z", + "iopub.status.idle": "2023-08-22T06:59:14.595399Z", + "shell.execute_reply": "2023-08-22T06:59:14.595111Z" } }, "outputs": [ @@ -3767,10 +3767,10 @@ "id": "2ba1d33d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.339714Z", - "iopub.status.busy": "2023-08-21T03:36:08.339640Z", - "iopub.status.idle": "2023-08-21T03:36:08.342116Z", - "shell.execute_reply": "2023-08-21T03:36:08.341883Z" + "iopub.execute_input": "2023-08-22T06:59:14.596985Z", + "iopub.status.busy": "2023-08-22T06:59:14.596880Z", + "iopub.status.idle": "2023-08-22T06:59:14.599760Z", + "shell.execute_reply": "2023-08-22T06:59:14.599435Z" }, "lines_to_next_cell": 2 }, @@ -3807,10 +3807,10 @@ "id": "3d03baab", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.343548Z", - "iopub.status.busy": "2023-08-21T03:36:08.343471Z", - "iopub.status.idle": "2023-08-21T03:36:08.345627Z", - "shell.execute_reply": "2023-08-21T03:36:08.345379Z" + "iopub.execute_input": "2023-08-22T06:59:14.602110Z", + "iopub.status.busy": "2023-08-22T06:59:14.601973Z", + "iopub.status.idle": "2023-08-22T06:59:14.604410Z", + "shell.execute_reply": "2023-08-22T06:59:14.604070Z" }, "lines_to_next_cell": 2 }, @@ -3851,10 +3851,10 @@ "id": "410b4dd7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.347031Z", - "iopub.status.busy": "2023-08-21T03:36:08.346955Z", - "iopub.status.idle": "2023-08-21T03:36:08.351303Z", - "shell.execute_reply": "2023-08-21T03:36:08.351081Z" + "iopub.execute_input": "2023-08-22T06:59:14.606098Z", + "iopub.status.busy": "2023-08-22T06:59:14.605987Z", + "iopub.status.idle": "2023-08-22T06:59:14.610632Z", + "shell.execute_reply": "2023-08-22T06:59:14.610234Z" }, "lines_to_next_cell": 0 }, @@ -3967,10 +3967,10 @@ "id": "3540804d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.352671Z", - "iopub.status.busy": "2023-08-21T03:36:08.352588Z", - "iopub.status.idle": "2023-08-21T03:36:08.365290Z", - "shell.execute_reply": "2023-08-21T03:36:08.365017Z" + "iopub.execute_input": "2023-08-22T06:59:14.612402Z", + "iopub.status.busy": "2023-08-22T06:59:14.612271Z", + "iopub.status.idle": "2023-08-22T06:59:14.625177Z", + "shell.execute_reply": "2023-08-22T06:59:14.624839Z" }, "lines_to_next_cell": 0 }, @@ -4854,10 +4854,10 @@ "id": "66d174f1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.366746Z", - "iopub.status.busy": "2023-08-21T03:36:08.366648Z", - "iopub.status.idle": "2023-08-21T03:36:08.371142Z", - "shell.execute_reply": "2023-08-21T03:36:08.370889Z" + "iopub.execute_input": "2023-08-22T06:59:14.626829Z", + "iopub.status.busy": "2023-08-22T06:59:14.626719Z", + "iopub.status.idle": "2023-08-22T06:59:14.631422Z", + "shell.execute_reply": "2023-08-22T06:59:14.631104Z" }, "lines_to_next_cell": 0 }, @@ -4989,10 +4989,10 @@ "id": "52789c77", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.372548Z", - "iopub.status.busy": "2023-08-21T03:36:08.372468Z", - "iopub.status.idle": "2023-08-21T03:36:08.374676Z", - "shell.execute_reply": "2023-08-21T03:36:08.374427Z" + "iopub.execute_input": "2023-08-22T06:59:14.633211Z", + "iopub.status.busy": "2023-08-22T06:59:14.633074Z", + "iopub.status.idle": "2023-08-22T06:59:14.635511Z", + "shell.execute_reply": "2023-08-22T06:59:14.635190Z" }, "lines_to_next_cell": 0 }, @@ -5030,10 +5030,10 @@ "id": "d83650bf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.376096Z", - "iopub.status.busy": "2023-08-21T03:36:08.376016Z", - "iopub.status.idle": "2023-08-21T03:36:08.382023Z", - "shell.execute_reply": "2023-08-21T03:36:08.381780Z" + "iopub.execute_input": "2023-08-22T06:59:14.637090Z", + "iopub.status.busy": "2023-08-22T06:59:14.636984Z", + "iopub.status.idle": "2023-08-22T06:59:14.643250Z", + "shell.execute_reply": "2023-08-22T06:59:14.642921Z" } }, "outputs": [ @@ -5254,10 +5254,10 @@ "id": "880d79d9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.383342Z", - "iopub.status.busy": "2023-08-21T03:36:08.383266Z", - "iopub.status.idle": "2023-08-21T03:36:08.385348Z", - "shell.execute_reply": "2023-08-21T03:36:08.385111Z" + "iopub.execute_input": "2023-08-22T06:59:14.644959Z", + "iopub.status.busy": "2023-08-22T06:59:14.644832Z", + "iopub.status.idle": "2023-08-22T06:59:14.647067Z", + "shell.execute_reply": "2023-08-22T06:59:14.646780Z" }, "lines_to_next_cell": 0 }, @@ -5297,10 +5297,10 @@ "id": "c01f4095", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.386800Z", - "iopub.status.busy": "2023-08-21T03:36:08.386719Z", - "iopub.status.idle": "2023-08-21T03:36:08.390900Z", - "shell.execute_reply": "2023-08-21T03:36:08.390675Z" + "iopub.execute_input": "2023-08-22T06:59:14.648616Z", + "iopub.status.busy": "2023-08-22T06:59:14.648506Z", + "iopub.status.idle": "2023-08-22T06:59:14.653020Z", + "shell.execute_reply": "2023-08-22T06:59:14.652673Z" }, "lines_to_next_cell": 0 }, @@ -5410,10 +5410,10 @@ "id": "a4202eb8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.392405Z", - "iopub.status.busy": "2023-08-21T03:36:08.392322Z", - "iopub.status.idle": "2023-08-21T03:36:08.396509Z", - "shell.execute_reply": "2023-08-21T03:36:08.396244Z" + "iopub.execute_input": "2023-08-22T06:59:14.654821Z", + "iopub.status.busy": "2023-08-22T06:59:14.654708Z", + "iopub.status.idle": "2023-08-22T06:59:14.658952Z", + "shell.execute_reply": "2023-08-22T06:59:14.658676Z" }, "lines_to_next_cell": 0 }, @@ -5522,10 +5522,10 @@ "id": "948b2d07", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.397917Z", - "iopub.status.busy": "2023-08-21T03:36:08.397838Z", - "iopub.status.idle": "2023-08-21T03:36:08.402447Z", - "shell.execute_reply": "2023-08-21T03:36:08.402192Z" + "iopub.execute_input": "2023-08-22T06:59:14.660688Z", + "iopub.status.busy": "2023-08-22T06:59:14.660582Z", + "iopub.status.idle": "2023-08-22T06:59:14.665683Z", + "shell.execute_reply": "2023-08-22T06:59:14.665320Z" }, "lines_to_next_cell": 0 }, @@ -5676,10 +5676,10 @@ "id": "1cfdcc5c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.403773Z", - "iopub.status.busy": "2023-08-21T03:36:08.403692Z", - "iopub.status.idle": "2023-08-21T03:36:08.407036Z", - "shell.execute_reply": "2023-08-21T03:36:08.406794Z" + "iopub.execute_input": "2023-08-22T06:59:14.667792Z", + "iopub.status.busy": "2023-08-22T06:59:14.667649Z", + "iopub.status.idle": "2023-08-22T06:59:14.672086Z", + "shell.execute_reply": "2023-08-22T06:59:14.671668Z" }, "lines_to_next_cell": 0 }, @@ -5763,10 +5763,10 @@ "id": "fd9c5cda", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.408461Z", - "iopub.status.busy": "2023-08-21T03:36:08.408387Z", - "iopub.status.idle": "2023-08-21T03:36:08.411673Z", - "shell.execute_reply": "2023-08-21T03:36:08.411429Z" + "iopub.execute_input": "2023-08-22T06:59:14.674155Z", + "iopub.status.busy": "2023-08-22T06:59:14.674020Z", + "iopub.status.idle": "2023-08-22T06:59:14.677900Z", + "shell.execute_reply": "2023-08-22T06:59:14.677570Z" }, "lines_to_next_cell": 0 }, @@ -5856,10 +5856,10 @@ "id": "6d431cb5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.413092Z", - "iopub.status.busy": "2023-08-21T03:36:08.413016Z", - "iopub.status.idle": "2023-08-21T03:36:08.418535Z", - "shell.execute_reply": "2023-08-21T03:36:08.418303Z" + "iopub.execute_input": "2023-08-22T06:59:14.679838Z", + "iopub.status.busy": "2023-08-22T06:59:14.679694Z", + "iopub.status.idle": "2023-08-22T06:59:14.685743Z", + "shell.execute_reply": "2023-08-22T06:59:14.685309Z" }, "lines_to_next_cell": 2 }, @@ -6276,10 +6276,10 @@ "id": "fac41ce1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.419882Z", - "iopub.status.busy": "2023-08-21T03:36:08.419806Z", - "iopub.status.idle": "2023-08-21T03:36:08.425319Z", - "shell.execute_reply": "2023-08-21T03:36:08.425073Z" + "iopub.execute_input": "2023-08-22T06:59:14.687552Z", + "iopub.status.busy": "2023-08-22T06:59:14.687421Z", + "iopub.status.idle": "2023-08-22T06:59:14.693477Z", + "shell.execute_reply": "2023-08-22T06:59:14.693157Z" }, "lines_to_next_cell": 0 }, @@ -6700,10 +6700,10 @@ "id": "b0885654", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.426701Z", - "iopub.status.busy": "2023-08-21T03:36:08.426621Z", - "iopub.status.idle": "2023-08-21T03:36:08.431378Z", - "shell.execute_reply": "2023-08-21T03:36:08.431148Z" + "iopub.execute_input": "2023-08-22T06:59:14.695271Z", + "iopub.status.busy": "2023-08-22T06:59:14.695116Z", + "iopub.status.idle": "2023-08-22T06:59:14.700210Z", + "shell.execute_reply": "2023-08-22T06:59:14.699919Z" }, "lines_to_next_cell": 0 }, @@ -6980,10 +6980,10 @@ "id": "213945a6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.432780Z", - "iopub.status.busy": "2023-08-21T03:36:08.432696Z", - "iopub.status.idle": "2023-08-21T03:36:08.438473Z", - "shell.execute_reply": "2023-08-21T03:36:08.438250Z" + "iopub.execute_input": "2023-08-22T06:59:14.702075Z", + "iopub.status.busy": "2023-08-22T06:59:14.701942Z", + "iopub.status.idle": "2023-08-22T06:59:14.708849Z", + "shell.execute_reply": "2023-08-22T06:59:14.708468Z" }, "lines_to_next_cell": 0 }, @@ -7371,10 +7371,10 @@ "id": "a3c4060a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.439902Z", - "iopub.status.busy": "2023-08-21T03:36:08.439825Z", - "iopub.status.idle": "2023-08-21T03:36:08.441707Z", - "shell.execute_reply": "2023-08-21T03:36:08.441464Z" + "iopub.execute_input": "2023-08-22T06:59:14.710560Z", + "iopub.status.busy": "2023-08-22T06:59:14.710418Z", + "iopub.status.idle": "2023-08-22T06:59:14.712662Z", + "shell.execute_reply": "2023-08-22T06:59:14.712379Z" }, "lines_to_next_cell": 0 }, @@ -7415,10 +7415,10 @@ "id": "f2bffb69", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.443349Z", - "iopub.status.busy": "2023-08-21T03:36:08.443241Z", - "iopub.status.idle": "2023-08-21T03:36:08.445173Z", - "shell.execute_reply": "2023-08-21T03:36:08.444935Z" + "iopub.execute_input": "2023-08-22T06:59:14.714548Z", + "iopub.status.busy": "2023-08-22T06:59:14.714416Z", + "iopub.status.idle": "2023-08-22T06:59:14.716724Z", + "shell.execute_reply": "2023-08-22T06:59:14.716275Z" }, "lines_to_next_cell": 0 }, @@ -7467,10 +7467,10 @@ "id": "ee827a53", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.446610Z", - "iopub.status.busy": "2023-08-21T03:36:08.446520Z", - "iopub.status.idle": "2023-08-21T03:36:08.448323Z", - "shell.execute_reply": "2023-08-21T03:36:08.448070Z" + "iopub.execute_input": "2023-08-22T06:59:14.718538Z", + "iopub.status.busy": "2023-08-22T06:59:14.718418Z", + "iopub.status.idle": "2023-08-22T06:59:14.720778Z", + "shell.execute_reply": "2023-08-22T06:59:14.720410Z" } }, "outputs": [ @@ -7522,10 +7522,10 @@ "id": "3a097fbc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.449714Z", - "iopub.status.busy": "2023-08-21T03:36:08.449623Z", - "iopub.status.idle": "2023-08-21T03:36:08.454097Z", - "shell.execute_reply": "2023-08-21T03:36:08.453813Z" + "iopub.execute_input": "2023-08-22T06:59:14.722745Z", + "iopub.status.busy": "2023-08-22T06:59:14.722445Z", + "iopub.status.idle": "2023-08-22T06:59:14.727643Z", + "shell.execute_reply": "2023-08-22T06:59:14.727302Z" }, "lines_to_next_cell": 2 }, @@ -7618,10 +7618,10 @@ "id": "e064e170", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.455528Z", - "iopub.status.busy": "2023-08-21T03:36:08.455447Z", - "iopub.status.idle": "2023-08-21T03:36:08.457783Z", - "shell.execute_reply": "2023-08-21T03:36:08.457543Z" + "iopub.execute_input": "2023-08-22T06:59:14.729283Z", + "iopub.status.busy": "2023-08-22T06:59:14.729148Z", + "iopub.status.idle": "2023-08-22T06:59:14.732019Z", + "shell.execute_reply": "2023-08-22T06:59:14.731599Z" }, "lines_to_next_cell": 0 }, @@ -7675,10 +7675,10 @@ "id": "c915ca52", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.459248Z", - "iopub.status.busy": "2023-08-21T03:36:08.459155Z", - "iopub.status.idle": "2023-08-21T03:36:08.552220Z", - "shell.execute_reply": "2023-08-21T03:36:08.551914Z" + "iopub.execute_input": "2023-08-22T06:59:14.733916Z", + "iopub.status.busy": "2023-08-22T06:59:14.733787Z", + "iopub.status.idle": "2023-08-22T06:59:14.823121Z", + "shell.execute_reply": "2023-08-22T06:59:14.822788Z" }, "lines_to_next_cell": 0 }, @@ -7724,10 +7724,10 @@ "id": "65cd6d02", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.553877Z", - "iopub.status.busy": "2023-08-21T03:36:08.553770Z", - "iopub.status.idle": "2023-08-21T03:36:08.640715Z", - "shell.execute_reply": "2023-08-21T03:36:08.640411Z" + "iopub.execute_input": "2023-08-22T06:59:14.825251Z", + "iopub.status.busy": "2023-08-22T06:59:14.825113Z", + "iopub.status.idle": "2023-08-22T06:59:14.905789Z", + "shell.execute_reply": "2023-08-22T06:59:14.905480Z" }, "lines_to_next_cell": 0 }, @@ -7766,10 +7766,10 @@ "id": "76b5c0b1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.642311Z", - "iopub.status.busy": "2023-08-21T03:36:08.642208Z", - "iopub.status.idle": "2023-08-21T03:36:08.737860Z", - "shell.execute_reply": "2023-08-21T03:36:08.737565Z" + "iopub.execute_input": "2023-08-22T06:59:14.907636Z", + "iopub.status.busy": "2023-08-22T06:59:14.907511Z", + "iopub.status.idle": "2023-08-22T06:59:14.997060Z", + "shell.execute_reply": "2023-08-22T06:59:14.996751Z" }, "lines_to_next_cell": 0 }, @@ -7806,10 +7806,10 @@ "id": "183a2c2b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.739490Z", - "iopub.status.busy": "2023-08-21T03:36:08.739374Z", - "iopub.status.idle": "2023-08-21T03:36:08.779690Z", - "shell.execute_reply": "2023-08-21T03:36:08.779420Z" + "iopub.execute_input": "2023-08-22T06:59:14.998844Z", + "iopub.status.busy": "2023-08-22T06:59:14.998722Z", + "iopub.status.idle": "2023-08-22T06:59:15.033680Z", + "shell.execute_reply": "2023-08-22T06:59:15.033292Z" } }, "outputs": [], @@ -7837,10 +7837,10 @@ "id": "75fbb981", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.781309Z", - "iopub.status.busy": "2023-08-21T03:36:08.781225Z", - "iopub.status.idle": "2023-08-21T03:36:08.949186Z", - "shell.execute_reply": "2023-08-21T03:36:08.948871Z" + "iopub.execute_input": "2023-08-22T06:59:15.035870Z", + "iopub.status.busy": "2023-08-22T06:59:15.035723Z", + "iopub.status.idle": "2023-08-22T06:59:15.198431Z", + "shell.execute_reply": "2023-08-22T06:59:15.198047Z" } }, "outputs": [ @@ -7885,10 +7885,10 @@ "id": "55b3a1cc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.950967Z", - "iopub.status.busy": "2023-08-21T03:36:08.950852Z", - "iopub.status.idle": "2023-08-21T03:36:08.953871Z", - "shell.execute_reply": "2023-08-21T03:36:08.953602Z" + "iopub.execute_input": "2023-08-22T06:59:15.200753Z", + "iopub.status.busy": "2023-08-22T06:59:15.200526Z", + "iopub.status.idle": "2023-08-22T06:59:15.203898Z", + "shell.execute_reply": "2023-08-22T06:59:15.203556Z" }, "lines_to_next_cell": 0 }, @@ -7924,10 +7924,10 @@ "id": "f3d88794", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:08.955394Z", - "iopub.status.busy": "2023-08-21T03:36:08.955297Z", - "iopub.status.idle": "2023-08-21T03:36:09.060746Z", - "shell.execute_reply": "2023-08-21T03:36:09.060425Z" + "iopub.execute_input": "2023-08-22T06:59:15.205746Z", + "iopub.status.busy": "2023-08-22T06:59:15.205652Z", + "iopub.status.idle": "2023-08-22T06:59:15.305674Z", + "shell.execute_reply": "2023-08-22T06:59:15.305240Z" } }, "outputs": [ @@ -7961,10 +7961,10 @@ "id": "eea49f5b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:09.062393Z", - "iopub.status.busy": "2023-08-21T03:36:09.062272Z", - "iopub.status.idle": "2023-08-21T03:36:09.164120Z", - "shell.execute_reply": "2023-08-21T03:36:09.163816Z" + "iopub.execute_input": "2023-08-22T06:59:15.307641Z", + "iopub.status.busy": "2023-08-22T06:59:15.307491Z", + "iopub.status.idle": "2023-08-22T06:59:15.405217Z", + "shell.execute_reply": "2023-08-22T06:59:15.404785Z" }, "lines_to_next_cell": 0 }, @@ -7999,10 +7999,10 @@ "id": "d5bcfff8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:09.165860Z", - "iopub.status.busy": "2023-08-21T03:36:09.165745Z", - "iopub.status.idle": "2023-08-21T03:36:09.262378Z", - "shell.execute_reply": "2023-08-21T03:36:09.262095Z" + "iopub.execute_input": "2023-08-22T06:59:15.407321Z", + "iopub.status.busy": "2023-08-22T06:59:15.407190Z", + "iopub.status.idle": "2023-08-22T06:59:15.503021Z", + "shell.execute_reply": "2023-08-22T06:59:15.502607Z" }, "lines_to_next_cell": 0 }, @@ -8041,10 +8041,10 @@ "id": "edb66cae", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:09.264050Z", - "iopub.status.busy": "2023-08-21T03:36:09.263936Z", - "iopub.status.idle": "2023-08-21T03:36:10.182139Z", - "shell.execute_reply": "2023-08-21T03:36:10.181842Z" + "iopub.execute_input": "2023-08-22T06:59:15.504880Z", + "iopub.status.busy": "2023-08-22T06:59:15.504746Z", + "iopub.status.idle": "2023-08-22T06:59:16.457367Z", + "shell.execute_reply": "2023-08-22T06:59:16.457033Z" }, "lines_to_next_cell": 0 }, @@ -8079,10 +8079,10 @@ "id": "4f5d25d9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:10.183868Z", - "iopub.status.busy": "2023-08-21T03:36:10.183754Z", - "iopub.status.idle": "2023-08-21T03:36:10.401318Z", - "shell.execute_reply": "2023-08-21T03:36:10.401033Z" + "iopub.execute_input": "2023-08-22T06:59:16.459211Z", + "iopub.status.busy": "2023-08-22T06:59:16.459087Z", + "iopub.status.idle": "2023-08-22T06:59:16.684825Z", + "shell.execute_reply": "2023-08-22T06:59:16.684501Z" }, "lines_to_next_cell": 0 }, @@ -8118,10 +8118,10 @@ "id": "ce7b23e2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:10.403067Z", - "iopub.status.busy": "2023-08-21T03:36:10.402953Z", - "iopub.status.idle": "2023-08-21T03:36:10.408957Z", - "shell.execute_reply": "2023-08-21T03:36:10.408683Z" + "iopub.execute_input": "2023-08-22T06:59:16.686592Z", + "iopub.status.busy": "2023-08-22T06:59:16.686475Z", + "iopub.status.idle": "2023-08-22T06:59:16.692382Z", + "shell.execute_reply": "2023-08-22T06:59:16.692013Z" }, "lines_to_next_cell": 0 }, @@ -8231,10 +8231,10 @@ "id": "a6545d2f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T03:36:10.410500Z", - "iopub.status.busy": "2023-08-21T03:36:10.410393Z", - "iopub.status.idle": "2023-08-21T03:36:10.414627Z", - "shell.execute_reply": "2023-08-21T03:36:10.414350Z" + "iopub.execute_input": "2023-08-22T06:59:16.694320Z", + "iopub.status.busy": "2023-08-22T06:59:16.694191Z", + "iopub.status.idle": "2023-08-22T06:59:16.698368Z", + "shell.execute_reply": "2023-08-22T06:59:16.698098Z" }, "lines_to_next_cell": 0 }, @@ -8278,7 +8278,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -8291,7 +8291,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch03-linreg-lab.Rmd b/Ch03-linreg-lab.Rmd index 930176c..afb1570 100644 --- a/Ch03-linreg-lab.Rmd +++ b/Ch03-linreg-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch03-linreg-lab.ipynb b/Ch03-linreg-lab.ipynb index f039622..78a516a 100644 --- a/Ch03-linreg-lab.ipynb +++ b/Ch03-linreg-lab.ipynb @@ -27,10 +27,10 @@ "id": "b18c1628", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:52.978537Z", - "iopub.status.busy": "2023-08-21T02:28:52.978403Z", - "iopub.status.idle": "2023-08-21T02:28:53.456488Z", - "shell.execute_reply": "2023-08-21T02:28:53.456172Z" + "iopub.execute_input": "2023-08-22T06:59:19.963803Z", + "iopub.status.busy": "2023-08-22T06:59:19.963695Z", + "iopub.status.idle": "2023-08-22T06:59:20.384511Z", + "shell.execute_reply": "2023-08-22T06:59:20.384219Z" }, "lines_to_next_cell": 2 }, @@ -60,10 +60,10 @@ "id": "a10a1d7d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:53.458574Z", - "iopub.status.busy": "2023-08-21T02:28:53.458356Z", - "iopub.status.idle": "2023-08-21T02:28:54.074306Z", - "shell.execute_reply": "2023-08-21T02:28:54.073950Z" + "iopub.execute_input": "2023-08-22T06:59:20.387117Z", + "iopub.status.busy": "2023-08-22T06:59:20.386932Z", + "iopub.status.idle": "2023-08-22T06:59:27.510372Z", + "shell.execute_reply": "2023-08-22T06:59:27.510076Z" }, "lines_to_next_cell": 0 }, @@ -93,10 +93,10 @@ "id": "756c0524", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.076206Z", - "iopub.status.busy": "2023-08-21T02:28:54.076055Z", - "iopub.status.idle": "2023-08-21T02:28:54.079277Z", - "shell.execute_reply": "2023-08-21T02:28:54.079022Z" + "iopub.execute_input": "2023-08-22T06:59:27.512280Z", + "iopub.status.busy": "2023-08-22T06:59:27.512129Z", + "iopub.status.idle": "2023-08-22T06:59:27.514850Z", + "shell.execute_reply": "2023-08-22T06:59:27.514531Z" } }, "outputs": [], @@ -124,10 +124,10 @@ "id": "2c370a6e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.080812Z", - "iopub.status.busy": "2023-08-21T02:28:54.080717Z", - "iopub.status.idle": "2023-08-21T02:28:54.212489Z", - "shell.execute_reply": "2023-08-21T02:28:54.212195Z" + "iopub.execute_input": "2023-08-22T06:59:27.516720Z", + "iopub.status.busy": "2023-08-22T06:59:27.516584Z", + "iopub.status.idle": "2023-08-22T06:59:30.213761Z", + "shell.execute_reply": "2023-08-22T06:59:30.213403Z" } }, "outputs": [], @@ -156,10 +156,10 @@ "id": "43bcb3a9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.214288Z", - "iopub.status.busy": "2023-08-21T02:28:54.214131Z", - "iopub.status.idle": "2023-08-21T02:28:54.218521Z", - "shell.execute_reply": "2023-08-21T02:28:54.217256Z" + "iopub.execute_input": "2023-08-22T06:59:30.215847Z", + "iopub.status.busy": "2023-08-22T06:59:30.215679Z", + "iopub.status.idle": "2023-08-22T06:59:30.219200Z", + "shell.execute_reply": "2023-08-22T06:59:30.218854Z" }, "lines_to_next_cell": 0 }, @@ -237,10 +237,10 @@ "id": "cb81bfb0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.228152Z", - "iopub.status.busy": "2023-08-21T02:28:54.227968Z", - "iopub.status.idle": "2023-08-21T02:28:54.231888Z", - "shell.execute_reply": "2023-08-21T02:28:54.231418Z" + "iopub.execute_input": "2023-08-22T06:59:30.220842Z", + "iopub.status.busy": "2023-08-22T06:59:30.220745Z", + "iopub.status.idle": "2023-08-22T06:59:30.223794Z", + "shell.execute_reply": "2023-08-22T06:59:30.223517Z" }, "lines_to_next_cell": 0 }, @@ -282,7 +282,6 @@ " '__ge__',\n", " '__getattribute__',\n", " '__getitem__',\n", - " '__getstate__',\n", " '__gt__',\n", " '__hash__',\n", " '__iadd__',\n", @@ -441,10 +440,10 @@ "id": "29e9bdab", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.233644Z", - "iopub.status.busy": "2023-08-21T02:28:54.233538Z", - "iopub.status.idle": "2023-08-21T02:28:54.236077Z", - "shell.execute_reply": "2023-08-21T02:28:54.235804Z" + "iopub.execute_input": "2023-08-22T06:59:30.225458Z", + "iopub.status.busy": "2023-08-22T06:59:30.225336Z", + "iopub.status.idle": "2023-08-22T06:59:30.227667Z", + "shell.execute_reply": "2023-08-22T06:59:30.227385Z" }, "lines_to_next_cell": 0 }, @@ -499,10 +498,10 @@ "id": "72a15de5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.237580Z", - "iopub.status.busy": "2023-08-21T02:28:54.237492Z", - "iopub.status.idle": "2023-08-21T02:28:54.242855Z", - "shell.execute_reply": "2023-08-21T02:28:54.242574Z" + "iopub.execute_input": "2023-08-22T06:59:30.229351Z", + "iopub.status.busy": "2023-08-22T06:59:30.229229Z", + "iopub.status.idle": "2023-08-22T06:59:30.233978Z", + "shell.execute_reply": "2023-08-22T06:59:30.233738Z" } }, "outputs": [ @@ -543,10 +542,10 @@ "id": "26837cfe", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.244219Z", - "iopub.status.busy": "2023-08-21T02:28:54.244127Z", - "iopub.status.idle": "2023-08-21T02:28:54.249714Z", - "shell.execute_reply": "2023-08-21T02:28:54.249432Z" + "iopub.execute_input": "2023-08-22T06:59:30.235692Z", + "iopub.status.busy": "2023-08-22T06:59:30.235572Z", + "iopub.status.idle": "2023-08-22T06:59:30.240548Z", + "shell.execute_reply": "2023-08-22T06:59:30.240254Z" } }, "outputs": [ @@ -633,10 +632,10 @@ "id": "c70cbdb5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.251263Z", - "iopub.status.busy": "2023-08-21T02:28:54.251136Z", - "iopub.status.idle": "2023-08-21T02:28:54.253671Z", - "shell.execute_reply": "2023-08-21T02:28:54.253397Z" + "iopub.execute_input": "2023-08-22T06:59:30.242180Z", + "iopub.status.busy": "2023-08-22T06:59:30.242082Z", + "iopub.status.idle": "2023-08-22T06:59:30.244423Z", + "shell.execute_reply": "2023-08-22T06:59:30.244043Z" }, "lines_to_next_cell": 0 }, @@ -668,10 +667,10 @@ "id": "6f2d7c78", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.255193Z", - "iopub.status.busy": "2023-08-21T02:28:54.255089Z", - "iopub.status.idle": "2023-08-21T02:28:54.314793Z", - "shell.execute_reply": "2023-08-21T02:28:54.314504Z" + "iopub.execute_input": "2023-08-22T06:59:30.246386Z", + "iopub.status.busy": "2023-08-22T06:59:30.246241Z", + "iopub.status.idle": "2023-08-22T06:59:30.304643Z", + "shell.execute_reply": "2023-08-22T06:59:30.304342Z" }, "lines_to_next_cell": 2 }, @@ -779,10 +778,10 @@ "id": "cdec4294", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.316521Z", - "iopub.status.busy": "2023-08-21T02:28:54.316363Z", - "iopub.status.idle": "2023-08-21T02:28:54.323224Z", - "shell.execute_reply": "2023-08-21T02:28:54.322970Z" + "iopub.execute_input": "2023-08-22T06:59:30.306725Z", + "iopub.status.busy": "2023-08-22T06:59:30.306537Z", + "iopub.status.idle": "2023-08-22T06:59:30.313928Z", + "shell.execute_reply": "2023-08-22T06:59:30.313612Z" }, "lines_to_next_cell": 0 }, @@ -874,10 +873,10 @@ "id": "edf2efcb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.324750Z", - "iopub.status.busy": "2023-08-21T02:28:54.324644Z", - "iopub.status.idle": "2023-08-21T02:28:54.330945Z", - "shell.execute_reply": "2023-08-21T02:28:54.330680Z" + "iopub.execute_input": "2023-08-22T06:59:30.316046Z", + "iopub.status.busy": "2023-08-22T06:59:30.315927Z", + "iopub.status.idle": "2023-08-22T06:59:30.322463Z", + "shell.execute_reply": "2023-08-22T06:59:30.322137Z" }, "lines_to_next_cell": 0 }, @@ -978,10 +977,10 @@ "id": "49fc8992", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.332402Z", - "iopub.status.busy": "2023-08-21T02:28:54.332319Z", - "iopub.status.idle": "2023-08-21T02:28:54.341724Z", - "shell.execute_reply": "2023-08-21T02:28:54.341409Z" + "iopub.execute_input": "2023-08-22T06:59:30.324453Z", + "iopub.status.busy": "2023-08-22T06:59:30.324311Z", + "iopub.status.idle": "2023-08-22T06:59:30.334219Z", + "shell.execute_reply": "2023-08-22T06:59:30.333881Z" } }, "outputs": [ @@ -1000,10 +999,10 @@ " Method: Least Squares F-statistic: 601.6\n", "\n", "\n", - " Date: Sun, 20 Aug 2023 Prob (F-statistic): 5.08e-88\n", + " Date: Mon, 21 Aug 2023 Prob (F-statistic): 5.08e-88\n", "\n", "\n", - " Time: 19:28:54 Log-Likelihood: -1641.5\n", + " Time: 23:59:30 Log-Likelihood: -1641.5\n", "\n", "\n", " No. Observations: 506 AIC: 3287.\n", @@ -1051,8 +1050,8 @@ "\\textbf{Dep. Variable:} & medv & \\textbf{ R-squared: } & 0.544 \\\\\n", "\\textbf{Model:} & OLS & \\textbf{ Adj. R-squared: } & 0.543 \\\\\n", "\\textbf{Method:} & Least Squares & \\textbf{ F-statistic: } & 601.6 \\\\\n", - "\\textbf{Date:} & Sun, 20 Aug 2023 & \\textbf{ Prob (F-statistic):} & 5.08e-88 \\\\\n", - "\\textbf{Time:} & 19:28:54 & \\textbf{ Log-Likelihood: } & -1641.5 \\\\\n", + "\\textbf{Date:} & Mon, 21 Aug 2023 & \\textbf{ Prob (F-statistic):} & 5.08e-88 \\\\\n", + "\\textbf{Time:} & 23:59:30 & \\textbf{ Log-Likelihood: } & -1641.5 \\\\\n", "\\textbf{No. Observations:} & 506 & \\textbf{ AIC: } & 3287. \\\\\n", "\\textbf{Df Residuals:} & 504 & \\textbf{ BIC: } & 3295. \\\\\n", "\\textbf{Df Model:} & 1 & \\textbf{ } & \\\\\n", @@ -1087,8 +1086,8 @@ "Dep. Variable: medv R-squared: 0.544\n", "Model: OLS Adj. R-squared: 0.543\n", "Method: Least Squares F-statistic: 601.6\n", - "Date: Sun, 20 Aug 2023 Prob (F-statistic): 5.08e-88\n", - "Time: 19:28:54 Log-Likelihood: -1641.5\n", + "Date: Mon, 21 Aug 2023 Prob (F-statistic): 5.08e-88\n", + "Time: 23:59:30 Log-Likelihood: -1641.5\n", "No. Observations: 506 AIC: 3287.\n", "Df Residuals: 504 BIC: 3295.\n", "Df Model: 1 \n", @@ -1134,10 +1133,10 @@ "id": "6d0f4c3a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.343317Z", - "iopub.status.busy": "2023-08-21T02:28:54.343206Z", - "iopub.status.idle": "2023-08-21T02:28:54.345604Z", - "shell.execute_reply": "2023-08-21T02:28:54.345339Z" + "iopub.execute_input": "2023-08-22T06:59:30.336071Z", + "iopub.status.busy": "2023-08-22T06:59:30.335936Z", + "iopub.status.idle": "2023-08-22T06:59:30.338769Z", + "shell.execute_reply": "2023-08-22T06:59:30.338416Z" }, "lines_to_next_cell": 2 }, @@ -1177,10 +1176,10 @@ "id": "132ffded", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.347097Z", - "iopub.status.busy": "2023-08-21T02:28:54.346984Z", - "iopub.status.idle": "2023-08-21T02:28:54.350802Z", - "shell.execute_reply": "2023-08-21T02:28:54.350563Z" + "iopub.execute_input": "2023-08-22T06:59:30.340661Z", + "iopub.status.busy": "2023-08-22T06:59:30.340521Z", + "iopub.status.idle": "2023-08-22T06:59:30.345095Z", + "shell.execute_reply": "2023-08-22T06:59:30.344737Z" } }, "outputs": [ @@ -1261,10 +1260,10 @@ "id": "b654a050", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.352369Z", - "iopub.status.busy": "2023-08-21T02:28:54.352275Z", - "iopub.status.idle": "2023-08-21T02:28:54.354743Z", - "shell.execute_reply": "2023-08-21T02:28:54.354502Z" + "iopub.execute_input": "2023-08-22T06:59:30.346874Z", + "iopub.status.busy": "2023-08-22T06:59:30.346735Z", + "iopub.status.idle": "2023-08-22T06:59:30.349291Z", + "shell.execute_reply": "2023-08-22T06:59:30.349007Z" }, "lines_to_next_cell": 0 }, @@ -1299,10 +1298,10 @@ "id": "148ed59d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.356140Z", - "iopub.status.busy": "2023-08-21T02:28:54.356063Z", - "iopub.status.idle": "2023-08-21T02:28:54.358315Z", - "shell.execute_reply": "2023-08-21T02:28:54.358059Z" + "iopub.execute_input": "2023-08-22T06:59:30.351073Z", + "iopub.status.busy": "2023-08-22T06:59:30.350934Z", + "iopub.status.idle": "2023-08-22T06:59:30.353516Z", + "shell.execute_reply": "2023-08-22T06:59:30.353225Z" }, "lines_to_next_cell": 0 }, @@ -1338,10 +1337,10 @@ "id": "d9d7b844", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.359757Z", - "iopub.status.busy": "2023-08-21T02:28:54.359678Z", - "iopub.status.idle": "2023-08-21T02:28:54.362165Z", - "shell.execute_reply": "2023-08-21T02:28:54.361908Z" + "iopub.execute_input": "2023-08-22T06:59:30.355404Z", + "iopub.status.busy": "2023-08-22T06:59:30.355267Z", + "iopub.status.idle": "2023-08-22T06:59:30.357759Z", + "shell.execute_reply": "2023-08-22T06:59:30.357461Z" }, "lines_to_next_cell": 0 }, @@ -1398,10 +1397,10 @@ "id": "79de2913", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.363741Z", - "iopub.status.busy": "2023-08-21T02:28:54.363634Z", - "iopub.status.idle": "2023-08-21T02:28:54.365531Z", - "shell.execute_reply": "2023-08-21T02:28:54.365292Z" + "iopub.execute_input": "2023-08-22T06:59:30.359458Z", + "iopub.status.busy": "2023-08-22T06:59:30.359349Z", + "iopub.status.idle": "2023-08-22T06:59:30.361244Z", + "shell.execute_reply": "2023-08-22T06:59:30.360996Z" }, "lines_to_next_cell": 0 }, @@ -1432,10 +1431,10 @@ "id": "a9b843c7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.366874Z", - "iopub.status.busy": "2023-08-21T02:28:54.366784Z", - "iopub.status.idle": "2023-08-21T02:28:54.368713Z", - "shell.execute_reply": "2023-08-21T02:28:54.368464Z" + "iopub.execute_input": "2023-08-22T06:59:30.362847Z", + "iopub.status.busy": "2023-08-22T06:59:30.362727Z", + "iopub.status.idle": "2023-08-22T06:59:30.364665Z", + "shell.execute_reply": "2023-08-22T06:59:30.364410Z" }, "lines_to_next_cell": 0 }, @@ -1472,10 +1471,10 @@ "id": "7e116800", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.370163Z", - "iopub.status.busy": "2023-08-21T02:28:54.370073Z", - "iopub.status.idle": "2023-08-21T02:28:54.466696Z", - "shell.execute_reply": "2023-08-21T02:28:54.466338Z" + "iopub.execute_input": "2023-08-22T06:59:30.366228Z", + "iopub.status.busy": "2023-08-22T06:59:30.366005Z", + "iopub.status.idle": "2023-08-22T06:59:30.451927Z", + "shell.execute_reply": "2023-08-22T06:59:30.451614Z" }, "lines_to_next_cell": 0 }, @@ -1536,10 +1535,10 @@ "id": "b524399e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.468561Z", - "iopub.status.busy": "2023-08-21T02:28:54.468356Z", - "iopub.status.idle": "2023-08-21T02:28:54.566644Z", - "shell.execute_reply": "2023-08-21T02:28:54.566337Z" + "iopub.execute_input": "2023-08-22T06:59:30.453712Z", + "iopub.status.busy": "2023-08-22T06:59:30.453582Z", + "iopub.status.idle": "2023-08-22T06:59:30.544088Z", + "shell.execute_reply": "2023-08-22T06:59:30.543647Z" }, "lines_to_next_cell": 0 }, @@ -1584,10 +1583,10 @@ "id": "8c95b6b0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.568423Z", - "iopub.status.busy": "2023-08-21T02:28:54.568307Z", - "iopub.status.idle": "2023-08-21T02:28:54.658553Z", - "shell.execute_reply": "2023-08-21T02:28:54.658267Z" + "iopub.execute_input": "2023-08-22T06:59:30.545979Z", + "iopub.status.busy": "2023-08-22T06:59:30.545829Z", + "iopub.status.idle": "2023-08-22T06:59:30.629333Z", + "shell.execute_reply": "2023-08-22T06:59:30.628907Z" }, "lines_to_next_cell": 0 }, @@ -1652,10 +1651,10 @@ "id": "04ed8362", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.660197Z", - "iopub.status.busy": "2023-08-21T02:28:54.660075Z", - "iopub.status.idle": "2023-08-21T02:28:54.672237Z", - "shell.execute_reply": "2023-08-21T02:28:54.671994Z" + "iopub.execute_input": "2023-08-22T06:59:30.631304Z", + "iopub.status.busy": "2023-08-22T06:59:30.631172Z", + "iopub.status.idle": "2023-08-22T06:59:30.643510Z", + "shell.execute_reply": "2023-08-22T06:59:30.643228Z" }, "lines_to_next_cell": 0 }, @@ -1750,10 +1749,10 @@ "id": "6483e190", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.673721Z", - "iopub.status.busy": "2023-08-21T02:28:54.673628Z", - "iopub.status.idle": "2023-08-21T02:28:54.676304Z", - "shell.execute_reply": "2023-08-21T02:28:54.675993Z" + "iopub.execute_input": "2023-08-22T06:59:30.645260Z", + "iopub.status.busy": "2023-08-22T06:59:30.645134Z", + "iopub.status.idle": "2023-08-22T06:59:30.647637Z", + "shell.execute_reply": "2023-08-22T06:59:30.647310Z" } }, "outputs": [ @@ -1790,10 +1789,10 @@ "id": "99a6f9d0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.677828Z", - "iopub.status.busy": "2023-08-21T02:28:54.677709Z", - "iopub.status.idle": "2023-08-21T02:28:54.696704Z", - "shell.execute_reply": "2023-08-21T02:28:54.696381Z" + "iopub.execute_input": "2023-08-22T06:59:30.649333Z", + "iopub.status.busy": "2023-08-22T06:59:30.649188Z", + "iopub.status.idle": "2023-08-22T06:59:30.667501Z", + "shell.execute_reply": "2023-08-22T06:59:30.667201Z" } }, "outputs": [ @@ -1966,10 +1965,10 @@ "id": "78cf55d0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.698261Z", - "iopub.status.busy": "2023-08-21T02:28:54.698177Z", - "iopub.status.idle": "2023-08-21T02:28:54.716362Z", - "shell.execute_reply": "2023-08-21T02:28:54.716082Z" + "iopub.execute_input": "2023-08-22T06:59:30.669290Z", + "iopub.status.busy": "2023-08-22T06:59:30.669145Z", + "iopub.status.idle": "2023-08-22T06:59:30.687452Z", + "shell.execute_reply": "2023-08-22T06:59:30.687132Z" } }, "outputs": [ @@ -2154,10 +2153,10 @@ "id": "902f6474", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.718076Z", - "iopub.status.busy": "2023-08-21T02:28:54.717951Z", - "iopub.status.idle": "2023-08-21T02:28:54.725146Z", - "shell.execute_reply": "2023-08-21T02:28:54.724859Z" + "iopub.execute_input": "2023-08-22T06:59:30.689227Z", + "iopub.status.busy": "2023-08-22T06:59:30.689072Z", + "iopub.status.idle": "2023-08-22T06:59:30.695976Z", + "shell.execute_reply": "2023-08-22T06:59:30.695604Z" }, "lines_to_next_cell": 0 }, @@ -2286,10 +2285,10 @@ "id": "ea1c88e9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.726658Z", - "iopub.status.busy": "2023-08-21T02:28:54.726565Z", - "iopub.status.idle": "2023-08-21T02:28:54.731850Z", - "shell.execute_reply": "2023-08-21T02:28:54.731595Z" + "iopub.execute_input": "2023-08-22T06:59:30.697875Z", + "iopub.status.busy": "2023-08-22T06:59:30.697744Z", + "iopub.status.idle": "2023-08-22T06:59:30.702854Z", + "shell.execute_reply": "2023-08-22T06:59:30.702396Z" }, "lines_to_next_cell": 0 }, @@ -2319,10 +2318,10 @@ "id": "e9ff159c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.733388Z", - "iopub.status.busy": "2023-08-21T02:28:54.733294Z", - "iopub.status.idle": "2023-08-21T02:28:54.747346Z", - "shell.execute_reply": "2023-08-21T02:28:54.747067Z" + "iopub.execute_input": "2023-08-22T06:59:30.705060Z", + "iopub.status.busy": "2023-08-22T06:59:30.704928Z", + "iopub.status.idle": "2023-08-22T06:59:30.718546Z", + "shell.execute_reply": "2023-08-22T06:59:30.718288Z" }, "lines_to_next_cell": 2 }, @@ -2427,10 +2426,10 @@ "id": "c98f54b2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.748856Z", - "iopub.status.busy": "2023-08-21T02:28:54.748774Z", - "iopub.status.idle": "2023-08-21T02:28:54.763149Z", - "shell.execute_reply": "2023-08-21T02:28:54.762853Z" + "iopub.execute_input": "2023-08-22T06:59:30.720315Z", + "iopub.status.busy": "2023-08-22T06:59:30.720166Z", + "iopub.status.idle": "2023-08-22T06:59:30.733544Z", + "shell.execute_reply": "2023-08-22T06:59:30.733105Z" }, "lines_to_next_cell": 0 }, @@ -2545,10 +2544,10 @@ "id": "53065cac", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.764924Z", - "iopub.status.busy": "2023-08-21T02:28:54.764796Z", - "iopub.status.idle": "2023-08-21T02:28:54.770846Z", - "shell.execute_reply": "2023-08-21T02:28:54.770578Z" + "iopub.execute_input": "2023-08-22T06:59:30.735632Z", + "iopub.status.busy": "2023-08-22T06:59:30.735509Z", + "iopub.status.idle": "2023-08-22T06:59:30.740862Z", + "shell.execute_reply": "2023-08-22T06:59:30.740579Z" }, "lines_to_next_cell": 0 }, @@ -2655,10 +2654,10 @@ "id": "8c654809", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.772408Z", - "iopub.status.busy": "2023-08-21T02:28:54.772296Z", - "iopub.status.idle": "2023-08-21T02:28:54.872389Z", - "shell.execute_reply": "2023-08-21T02:28:54.872086Z" + "iopub.execute_input": "2023-08-22T06:59:30.742508Z", + "iopub.status.busy": "2023-08-22T06:59:30.742387Z", + "iopub.status.idle": "2023-08-22T06:59:30.835769Z", + "shell.execute_reply": "2023-08-22T06:59:30.835368Z" }, "lines_to_next_cell": 0 }, @@ -2666,7 +2665,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 34, @@ -2721,10 +2720,10 @@ "id": "2182f0ec", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.874000Z", - "iopub.status.busy": "2023-08-21T02:28:54.873893Z", - "iopub.status.idle": "2023-08-21T02:28:54.879085Z", - "shell.execute_reply": "2023-08-21T02:28:54.878817Z" + "iopub.execute_input": "2023-08-22T06:59:30.837767Z", + "iopub.status.busy": "2023-08-22T06:59:30.837636Z", + "iopub.status.idle": "2023-08-22T06:59:30.842380Z", + "shell.execute_reply": "2023-08-22T06:59:30.842026Z" }, "lines_to_next_cell": 0 }, @@ -2772,10 +2771,10 @@ "id": "d614fdcb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:54.880583Z", - "iopub.status.busy": "2023-08-21T02:28:54.880499Z", - "iopub.status.idle": "2023-08-21T02:28:54.907341Z", - "shell.execute_reply": "2023-08-21T02:28:54.907079Z" + "iopub.execute_input": "2023-08-22T06:59:30.844518Z", + "iopub.status.busy": "2023-08-22T06:59:30.844367Z", + "iopub.status.idle": "2023-08-22T06:59:30.871405Z", + "shell.execute_reply": "2023-08-22T06:59:30.871052Z" }, "lines_to_next_cell": 0 }, @@ -2967,7 +2966,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -2980,7 +2979,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch04-classification-lab.Rmd b/Ch04-classification-lab.Rmd index d3d8eec..de81f30 100644 --- a/Ch04-classification-lab.Rmd +++ b/Ch04-classification-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch04-classification-lab.ipynb b/Ch04-classification-lab.ipynb index 0ab61a0..eaa27c9 100644 --- a/Ch04-classification-lab.ipynb +++ b/Ch04-classification-lab.ipynb @@ -46,10 +46,10 @@ "id": "95d28c33", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:56.229892Z", - "iopub.status.busy": "2023-08-21T02:28:56.229672Z", - "iopub.status.idle": "2023-08-21T02:28:57.250402Z", - "shell.execute_reply": "2023-08-21T02:28:57.249963Z" + "iopub.execute_input": "2023-08-22T06:59:34.104356Z", + "iopub.status.busy": "2023-08-22T06:59:34.104253Z", + "iopub.status.idle": "2023-08-22T06:59:35.054094Z", + "shell.execute_reply": "2023-08-22T06:59:35.053754Z" } }, "outputs": [], @@ -77,10 +77,10 @@ "id": "f7fb5f2a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.252390Z", - "iopub.status.busy": "2023-08-21T02:28:57.252224Z", - "iopub.status.idle": "2023-08-21T02:28:57.272851Z", - "shell.execute_reply": "2023-08-21T02:28:57.272588Z" + "iopub.execute_input": "2023-08-22T06:59:35.056108Z", + "iopub.status.busy": "2023-08-22T06:59:35.055950Z", + "iopub.status.idle": "2023-08-22T06:59:35.206682Z", + "shell.execute_reply": "2023-08-22T06:59:35.206381Z" }, "lines_to_next_cell": 2 }, @@ -112,10 +112,10 @@ "id": "7845390b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.274355Z", - "iopub.status.busy": "2023-08-21T02:28:57.274258Z", - "iopub.status.idle": "2023-08-21T02:28:57.285160Z", - "shell.execute_reply": "2023-08-21T02:28:57.284894Z" + "iopub.execute_input": "2023-08-22T06:59:35.208609Z", + "iopub.status.busy": "2023-08-22T06:59:35.208499Z", + "iopub.status.idle": "2023-08-22T06:59:35.218856Z", + "shell.execute_reply": "2023-08-22T06:59:35.218543Z" }, "lines_to_next_cell": 0 }, @@ -332,10 +332,10 @@ "id": "a92e287a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.286715Z", - "iopub.status.busy": "2023-08-21T02:28:57.286616Z", - "iopub.status.idle": "2023-08-21T02:28:57.288883Z", - "shell.execute_reply": "2023-08-21T02:28:57.288648Z" + "iopub.execute_input": "2023-08-22T06:59:35.220822Z", + "iopub.status.busy": "2023-08-22T06:59:35.220658Z", + "iopub.status.idle": "2023-08-22T06:59:35.223146Z", + "shell.execute_reply": "2023-08-22T06:59:35.222864Z" }, "lines_to_next_cell": 0 }, @@ -376,10 +376,10 @@ "id": "96bb1e00", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.290357Z", - "iopub.status.busy": "2023-08-21T02:28:57.290259Z", - "iopub.status.idle": "2023-08-21T02:28:57.295352Z", - "shell.execute_reply": "2023-08-21T02:28:57.295083Z" + "iopub.execute_input": "2023-08-22T06:59:35.224965Z", + "iopub.status.busy": "2023-08-22T06:59:35.224831Z", + "iopub.status.idle": "2023-08-22T06:59:35.229701Z", + "shell.execute_reply": "2023-08-22T06:59:35.229442Z" }, "lines_to_next_cell": 0 }, @@ -557,10 +557,10 @@ "id": "4ddb96ba", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.296784Z", - "iopub.status.busy": "2023-08-21T02:28:57.296683Z", - "iopub.status.idle": "2023-08-21T02:28:57.392956Z", - "shell.execute_reply": "2023-08-21T02:28:57.392526Z" + "iopub.execute_input": "2023-08-22T06:59:35.231485Z", + "iopub.status.busy": "2023-08-22T06:59:35.231354Z", + "iopub.status.idle": "2023-08-22T06:59:35.319629Z", + "shell.execute_reply": "2023-08-22T06:59:35.319199Z" }, "lines_to_next_cell": 2 }, @@ -604,10 +604,10 @@ "id": "df59bcac", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.394870Z", - "iopub.status.busy": "2023-08-21T02:28:57.394721Z", - "iopub.status.idle": "2023-08-21T02:28:57.461746Z", - "shell.execute_reply": "2023-08-21T02:28:57.461390Z" + "iopub.execute_input": "2023-08-22T06:59:35.321733Z", + "iopub.status.busy": "2023-08-22T06:59:35.321597Z", + "iopub.status.idle": "2023-08-22T06:59:35.382350Z", + "shell.execute_reply": "2023-08-22T06:59:35.381919Z" }, "lines_to_next_cell": 0 }, @@ -744,10 +744,10 @@ "id": "f45f26de", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.463719Z", - "iopub.status.busy": "2023-08-21T02:28:57.463515Z", - "iopub.status.idle": "2023-08-21T02:28:57.466512Z", - "shell.execute_reply": "2023-08-21T02:28:57.466227Z" + "iopub.execute_input": "2023-08-22T06:59:35.384570Z", + "iopub.status.busy": "2023-08-22T06:59:35.384386Z", + "iopub.status.idle": "2023-08-22T06:59:35.387199Z", + "shell.execute_reply": "2023-08-22T06:59:35.386864Z" }, "lines_to_next_cell": 0 }, @@ -789,10 +789,10 @@ "id": "e9f38895", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.468254Z", - "iopub.status.busy": "2023-08-21T02:28:57.468113Z", - "iopub.status.idle": "2023-08-21T02:28:57.470717Z", - "shell.execute_reply": "2023-08-21T02:28:57.470403Z" + "iopub.execute_input": "2023-08-22T06:59:35.388777Z", + "iopub.status.busy": "2023-08-22T06:59:35.388675Z", + "iopub.status.idle": "2023-08-22T06:59:35.391038Z", + "shell.execute_reply": "2023-08-22T06:59:35.390743Z" } }, "outputs": [ @@ -840,10 +840,10 @@ "id": "4f20356d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.472719Z", - "iopub.status.busy": "2023-08-21T02:28:57.472578Z", - "iopub.status.idle": "2023-08-21T02:28:57.475369Z", - "shell.execute_reply": "2023-08-21T02:28:57.475043Z" + "iopub.execute_input": "2023-08-22T06:59:35.392617Z", + "iopub.status.busy": "2023-08-22T06:59:35.392475Z", + "iopub.status.idle": "2023-08-22T06:59:35.395311Z", + "shell.execute_reply": "2023-08-22T06:59:35.395042Z" }, "lines_to_next_cell": 0 }, @@ -884,10 +884,10 @@ "id": "152b3063", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.477166Z", - "iopub.status.busy": "2023-08-21T02:28:57.477052Z", - "iopub.status.idle": "2023-08-21T02:28:57.479161Z", - "shell.execute_reply": "2023-08-21T02:28:57.478803Z" + "iopub.execute_input": "2023-08-22T06:59:35.396940Z", + "iopub.status.busy": "2023-08-22T06:59:35.396826Z", + "iopub.status.idle": "2023-08-22T06:59:35.398854Z", + "shell.execute_reply": "2023-08-22T06:59:35.398548Z" }, "lines_to_next_cell": 0 }, @@ -917,10 +917,10 @@ "id": "0f89f7ae", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.480867Z", - "iopub.status.busy": "2023-08-21T02:28:57.480737Z", - "iopub.status.idle": "2023-08-21T02:28:57.487133Z", - "shell.execute_reply": "2023-08-21T02:28:57.486778Z" + "iopub.execute_input": "2023-08-22T06:59:35.400476Z", + "iopub.status.busy": "2023-08-22T06:59:35.400370Z", + "iopub.status.idle": "2023-08-22T06:59:35.406304Z", + "shell.execute_reply": "2023-08-22T06:59:35.405994Z" } }, "outputs": [ @@ -1006,10 +1006,10 @@ "id": "d55dd7ec", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.488873Z", - "iopub.status.busy": "2023-08-21T02:28:57.488756Z", - "iopub.status.idle": "2023-08-21T02:28:57.491458Z", - "shell.execute_reply": "2023-08-21T02:28:57.491162Z" + "iopub.execute_input": "2023-08-22T06:59:35.408001Z", + "iopub.status.busy": "2023-08-22T06:59:35.407888Z", + "iopub.status.idle": "2023-08-22T06:59:35.410520Z", + "shell.execute_reply": "2023-08-22T06:59:35.410222Z" }, "lines_to_next_cell": 0 }, @@ -1069,10 +1069,10 @@ "id": "b998a060", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.493306Z", - "iopub.status.busy": "2023-08-21T02:28:57.493174Z", - "iopub.status.idle": "2023-08-21T02:28:57.496464Z", - "shell.execute_reply": "2023-08-21T02:28:57.496107Z" + "iopub.execute_input": "2023-08-22T06:59:35.412348Z", + "iopub.status.busy": "2023-08-22T06:59:35.412200Z", + "iopub.status.idle": "2023-08-22T06:59:35.415670Z", + "shell.execute_reply": "2023-08-22T06:59:35.415360Z" }, "lines_to_next_cell": 2 }, @@ -1135,10 +1135,10 @@ "id": "814e34ce", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.498135Z", - "iopub.status.busy": "2023-08-21T02:28:57.498043Z", - "iopub.status.idle": "2023-08-21T02:28:57.502996Z", - "shell.execute_reply": "2023-08-21T02:28:57.502676Z" + "iopub.execute_input": "2023-08-22T06:59:35.417692Z", + "iopub.status.busy": "2023-08-22T06:59:35.417600Z", + "iopub.status.idle": "2023-08-22T06:59:35.422315Z", + "shell.execute_reply": "2023-08-22T06:59:35.421995Z" } }, "outputs": [], @@ -1172,10 +1172,10 @@ "id": "644823f9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.504874Z", - "iopub.status.busy": "2023-08-21T02:28:57.504743Z", - "iopub.status.idle": "2023-08-21T02:28:57.506879Z", - "shell.execute_reply": "2023-08-21T02:28:57.506558Z" + "iopub.execute_input": "2023-08-22T06:59:35.424241Z", + "iopub.status.busy": "2023-08-22T06:59:35.424099Z", + "iopub.status.idle": "2023-08-22T06:59:35.426371Z", + "shell.execute_reply": "2023-08-22T06:59:35.425999Z" }, "lines_to_next_cell": 0 }, @@ -1201,10 +1201,10 @@ "id": "51217c85", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.508502Z", - "iopub.status.busy": "2023-08-21T02:28:57.508403Z", - "iopub.status.idle": "2023-08-21T02:28:57.512973Z", - "shell.execute_reply": "2023-08-21T02:28:57.512720Z" + "iopub.execute_input": "2023-08-22T06:59:35.428375Z", + "iopub.status.busy": "2023-08-22T06:59:35.428239Z", + "iopub.status.idle": "2023-08-22T06:59:35.432849Z", + "shell.execute_reply": "2023-08-22T06:59:35.432491Z" }, "lines_to_next_cell": 0 }, @@ -1286,10 +1286,10 @@ "id": "a73446bf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.514459Z", - "iopub.status.busy": "2023-08-21T02:28:57.514377Z", - "iopub.status.idle": "2023-08-21T02:28:57.517011Z", - "shell.execute_reply": "2023-08-21T02:28:57.516758Z" + "iopub.execute_input": "2023-08-22T06:59:35.434489Z", + "iopub.status.busy": "2023-08-22T06:59:35.434371Z", + "iopub.status.idle": "2023-08-22T06:59:35.437237Z", + "shell.execute_reply": "2023-08-22T06:59:35.436914Z" }, "lines_to_next_cell": 2 }, @@ -1344,10 +1344,10 @@ "id": "8174767d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.518464Z", - "iopub.status.busy": "2023-08-21T02:28:57.518363Z", - "iopub.status.idle": "2023-08-21T02:28:57.528289Z", - "shell.execute_reply": "2023-08-21T02:28:57.527983Z" + "iopub.execute_input": "2023-08-22T06:59:35.439129Z", + "iopub.status.busy": "2023-08-22T06:59:35.438980Z", + "iopub.status.idle": "2023-08-22T06:59:35.449036Z", + "shell.execute_reply": "2023-08-22T06:59:35.448757Z" }, "lines_to_next_cell": 2 }, @@ -1438,10 +1438,10 @@ "id": "cba7e815", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.529915Z", - "iopub.status.busy": "2023-08-21T02:28:57.529812Z", - "iopub.status.idle": "2023-08-21T02:28:57.532108Z", - "shell.execute_reply": "2023-08-21T02:28:57.531849Z" + "iopub.execute_input": "2023-08-22T06:59:35.450840Z", + "iopub.status.busy": "2023-08-22T06:59:35.450725Z", + "iopub.status.idle": "2023-08-22T06:59:35.452944Z", + "shell.execute_reply": "2023-08-22T06:59:35.452674Z" } }, "outputs": [ @@ -1492,10 +1492,10 @@ "id": "97993185", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.533565Z", - "iopub.status.busy": "2023-08-21T02:28:57.533462Z", - "iopub.status.idle": "2023-08-21T02:28:57.537458Z", - "shell.execute_reply": "2023-08-21T02:28:57.537180Z" + "iopub.execute_input": "2023-08-22T06:59:35.454539Z", + "iopub.status.busy": "2023-08-22T06:59:35.454423Z", + "iopub.status.idle": "2023-08-22T06:59:35.458834Z", + "shell.execute_reply": "2023-08-22T06:59:35.458553Z" }, "lines_to_next_cell": 2 }, @@ -1544,10 +1544,10 @@ "id": "4bc774e9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.539054Z", - "iopub.status.busy": "2023-08-21T02:28:57.538952Z", - "iopub.status.idle": "2023-08-21T02:28:57.540857Z", - "shell.execute_reply": "2023-08-21T02:28:57.540537Z" + "iopub.execute_input": "2023-08-22T06:59:35.460658Z", + "iopub.status.busy": "2023-08-22T06:59:35.460534Z", + "iopub.status.idle": "2023-08-22T06:59:35.462216Z", + "shell.execute_reply": "2023-08-22T06:59:35.461957Z" } }, "outputs": [], @@ -1572,10 +1572,10 @@ "id": "8c6c0723", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.542568Z", - "iopub.status.busy": "2023-08-21T02:28:57.542481Z", - "iopub.status.idle": "2023-08-21T02:28:57.548927Z", - "shell.execute_reply": "2023-08-21T02:28:57.548581Z" + "iopub.execute_input": "2023-08-22T06:59:35.463858Z", + "iopub.status.busy": "2023-08-22T06:59:35.463759Z", + "iopub.status.idle": "2023-08-22T06:59:35.469987Z", + "shell.execute_reply": "2023-08-22T06:59:35.469710Z" }, "lines_to_next_cell": 0 }, @@ -1628,10 +1628,10 @@ "id": "cf8fd5ac", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.550601Z", - "iopub.status.busy": "2023-08-21T02:28:57.550496Z", - "iopub.status.idle": "2023-08-21T02:28:57.552737Z", - "shell.execute_reply": "2023-08-21T02:28:57.552471Z" + "iopub.execute_input": "2023-08-22T06:59:35.471584Z", + "iopub.status.busy": "2023-08-22T06:59:35.471470Z", + "iopub.status.idle": "2023-08-22T06:59:35.473834Z", + "shell.execute_reply": "2023-08-22T06:59:35.473552Z" }, "lines_to_next_cell": 2 }, @@ -1669,10 +1669,10 @@ "id": "bfd6b3f8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.554217Z", - "iopub.status.busy": "2023-08-21T02:28:57.554117Z", - "iopub.status.idle": "2023-08-21T02:28:57.556249Z", - "shell.execute_reply": "2023-08-21T02:28:57.555998Z" + "iopub.execute_input": "2023-08-22T06:59:35.475293Z", + "iopub.status.busy": "2023-08-22T06:59:35.475189Z", + "iopub.status.idle": "2023-08-22T06:59:35.477448Z", + "shell.execute_reply": "2023-08-22T06:59:35.477007Z" }, "lines_to_next_cell": 2 }, @@ -1707,10 +1707,10 @@ "id": "a1f75de4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.557716Z", - "iopub.status.busy": "2023-08-21T02:28:57.557623Z", - "iopub.status.idle": "2023-08-21T02:28:57.559886Z", - "shell.execute_reply": "2023-08-21T02:28:57.559582Z" + "iopub.execute_input": "2023-08-22T06:59:35.479354Z", + "iopub.status.busy": "2023-08-22T06:59:35.479219Z", + "iopub.status.idle": "2023-08-22T06:59:35.481609Z", + "shell.execute_reply": "2023-08-22T06:59:35.481305Z" }, "lines_to_next_cell": 2 }, @@ -1744,10 +1744,10 @@ "id": "82794178", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.561606Z", - "iopub.status.busy": "2023-08-21T02:28:57.561489Z", - "iopub.status.idle": "2023-08-21T02:28:57.563996Z", - "shell.execute_reply": "2023-08-21T02:28:57.563652Z" + "iopub.execute_input": "2023-08-22T06:59:35.483264Z", + "iopub.status.busy": "2023-08-22T06:59:35.483156Z", + "iopub.status.idle": "2023-08-22T06:59:35.485247Z", + "shell.execute_reply": "2023-08-22T06:59:35.484948Z" } }, "outputs": [ @@ -1782,10 +1782,10 @@ "id": "9b571047", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.565689Z", - "iopub.status.busy": "2023-08-21T02:28:57.565573Z", - "iopub.status.idle": "2023-08-21T02:28:57.568080Z", - "shell.execute_reply": "2023-08-21T02:28:57.567748Z" + "iopub.execute_input": "2023-08-22T06:59:35.486831Z", + "iopub.status.busy": "2023-08-22T06:59:35.486719Z", + "iopub.status.idle": "2023-08-22T06:59:35.489231Z", + "shell.execute_reply": "2023-08-22T06:59:35.488879Z" } }, "outputs": [], @@ -1809,10 +1809,10 @@ "id": "60f3d13a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.569793Z", - "iopub.status.busy": "2023-08-21T02:28:57.569674Z", - "iopub.status.idle": "2023-08-21T02:28:57.574322Z", - "shell.execute_reply": "2023-08-21T02:28:57.573986Z" + "iopub.execute_input": "2023-08-22T06:59:35.490888Z", + "iopub.status.busy": "2023-08-22T06:59:35.490781Z", + "iopub.status.idle": "2023-08-22T06:59:35.494972Z", + "shell.execute_reply": "2023-08-22T06:59:35.494699Z" }, "lines_to_next_cell": 2 }, @@ -1896,10 +1896,10 @@ "id": "96e680d9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.576103Z", - "iopub.status.busy": "2023-08-21T02:28:57.575991Z", - "iopub.status.idle": "2023-08-21T02:28:57.579068Z", - "shell.execute_reply": "2023-08-21T02:28:57.578805Z" + "iopub.execute_input": "2023-08-22T06:59:35.496550Z", + "iopub.status.busy": "2023-08-22T06:59:35.496460Z", + "iopub.status.idle": "2023-08-22T06:59:35.500050Z", + "shell.execute_reply": "2023-08-22T06:59:35.499652Z" }, "lines_to_next_cell": 2 }, @@ -1940,10 +1940,10 @@ "id": "b6695125", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.580746Z", - "iopub.status.busy": "2023-08-21T02:28:57.580639Z", - "iopub.status.idle": "2023-08-21T02:28:57.583327Z", - "shell.execute_reply": "2023-08-21T02:28:57.583073Z" + "iopub.execute_input": "2023-08-22T06:59:35.501821Z", + "iopub.status.busy": "2023-08-22T06:59:35.501696Z", + "iopub.status.idle": "2023-08-22T06:59:35.504118Z", + "shell.execute_reply": "2023-08-22T06:59:35.503779Z" }, "lines_to_next_cell": 2 }, @@ -1986,10 +1986,10 @@ "id": "3f38a14e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.584834Z", - "iopub.status.busy": "2023-08-21T02:28:57.584748Z", - "iopub.status.idle": "2023-08-21T02:28:57.587140Z", - "shell.execute_reply": "2023-08-21T02:28:57.586884Z" + "iopub.execute_input": "2023-08-22T06:59:35.505774Z", + "iopub.status.busy": "2023-08-22T06:59:35.505669Z", + "iopub.status.idle": "2023-08-22T06:59:35.508018Z", + "shell.execute_reply": "2023-08-22T06:59:35.507737Z" } }, "outputs": [ @@ -2051,10 +2051,10 @@ "id": "9b645803", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.588684Z", - "iopub.status.busy": "2023-08-21T02:28:57.588575Z", - "iopub.status.idle": "2023-08-21T02:28:57.592433Z", - "shell.execute_reply": "2023-08-21T02:28:57.592165Z" + "iopub.execute_input": "2023-08-22T06:59:35.510093Z", + "iopub.status.busy": "2023-08-22T06:59:35.509967Z", + "iopub.status.idle": "2023-08-22T06:59:35.514060Z", + "shell.execute_reply": "2023-08-22T06:59:35.513746Z" } }, "outputs": [ @@ -2091,10 +2091,10 @@ "id": "abfae544", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.593864Z", - "iopub.status.busy": "2023-08-21T02:28:57.593784Z", - "iopub.status.idle": "2023-08-21T02:28:57.596074Z", - "shell.execute_reply": "2023-08-21T02:28:57.595807Z" + "iopub.execute_input": "2023-08-22T06:59:35.515774Z", + "iopub.status.busy": "2023-08-22T06:59:35.515682Z", + "iopub.status.idle": "2023-08-22T06:59:35.518169Z", + "shell.execute_reply": "2023-08-22T06:59:35.517903Z" } }, "outputs": [ @@ -2130,10 +2130,10 @@ "id": "2a3bb41e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.597540Z", - "iopub.status.busy": "2023-08-21T02:28:57.597455Z", - "iopub.status.idle": "2023-08-21T02:28:57.599658Z", - "shell.execute_reply": "2023-08-21T02:28:57.599399Z" + "iopub.execute_input": "2023-08-22T06:59:35.519953Z", + "iopub.status.busy": "2023-08-22T06:59:35.519849Z", + "iopub.status.idle": "2023-08-22T06:59:35.522248Z", + "shell.execute_reply": "2023-08-22T06:59:35.521930Z" }, "lines_to_next_cell": 0 }, @@ -2172,10 +2172,10 @@ "id": "1c64310b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.601097Z", - "iopub.status.busy": "2023-08-21T02:28:57.601019Z", - "iopub.status.idle": "2023-08-21T02:28:57.605729Z", - "shell.execute_reply": "2023-08-21T02:28:57.605444Z" + "iopub.execute_input": "2023-08-22T06:59:35.523826Z", + "iopub.status.busy": "2023-08-22T06:59:35.523714Z", + "iopub.status.idle": "2023-08-22T06:59:35.528214Z", + "shell.execute_reply": "2023-08-22T06:59:35.527959Z" }, "lines_to_next_cell": 0 }, @@ -2257,10 +2257,10 @@ "id": "0c05c5a8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.607207Z", - "iopub.status.busy": "2023-08-21T02:28:57.607093Z", - "iopub.status.idle": "2023-08-21T02:28:57.609626Z", - "shell.execute_reply": "2023-08-21T02:28:57.609348Z" + "iopub.execute_input": "2023-08-22T06:59:35.530152Z", + "iopub.status.busy": "2023-08-22T06:59:35.530024Z", + "iopub.status.idle": "2023-08-22T06:59:35.532713Z", + "shell.execute_reply": "2023-08-22T06:59:35.532375Z" }, "lines_to_next_cell": 2 }, @@ -2313,10 +2313,10 @@ "id": "47d85305", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.611305Z", - "iopub.status.busy": "2023-08-21T02:28:57.611177Z", - "iopub.status.idle": "2023-08-21T02:28:57.615527Z", - "shell.execute_reply": "2023-08-21T02:28:57.615221Z" + "iopub.execute_input": "2023-08-22T06:59:35.534353Z", + "iopub.status.busy": "2023-08-22T06:59:35.534232Z", + "iopub.status.idle": "2023-08-22T06:59:35.537918Z", + "shell.execute_reply": "2023-08-22T06:59:35.537612Z" }, "lines_to_next_cell": 2 }, @@ -2354,10 +2354,10 @@ "id": "c553aadf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.617346Z", - "iopub.status.busy": "2023-08-21T02:28:57.617202Z", - "iopub.status.idle": "2023-08-21T02:28:57.619612Z", - "shell.execute_reply": "2023-08-21T02:28:57.619301Z" + "iopub.execute_input": "2023-08-22T06:59:35.539480Z", + "iopub.status.busy": "2023-08-22T06:59:35.539391Z", + "iopub.status.idle": "2023-08-22T06:59:35.541924Z", + "shell.execute_reply": "2023-08-22T06:59:35.541560Z" }, "lines_to_next_cell": 2 }, @@ -2391,10 +2391,10 @@ "id": "4604bd3d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.621294Z", - "iopub.status.busy": "2023-08-21T02:28:57.621168Z", - "iopub.status.idle": "2023-08-21T02:28:57.623355Z", - "shell.execute_reply": "2023-08-21T02:28:57.623086Z" + "iopub.execute_input": "2023-08-22T06:59:35.543604Z", + "iopub.status.busy": "2023-08-22T06:59:35.543514Z", + "iopub.status.idle": "2023-08-22T06:59:35.545770Z", + "shell.execute_reply": "2023-08-22T06:59:35.545483Z" }, "lines_to_next_cell": 2 }, @@ -2430,10 +2430,10 @@ "id": "5ac2cabe", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.624902Z", - "iopub.status.busy": "2023-08-21T02:28:57.624775Z", - "iopub.status.idle": "2023-08-21T02:28:57.627201Z", - "shell.execute_reply": "2023-08-21T02:28:57.626911Z" + "iopub.execute_input": "2023-08-22T06:59:35.547333Z", + "iopub.status.busy": "2023-08-22T06:59:35.547227Z", + "iopub.status.idle": "2023-08-22T06:59:35.549381Z", + "shell.execute_reply": "2023-08-22T06:59:35.549124Z" } }, "outputs": [ @@ -2467,10 +2467,10 @@ "id": "f8623945", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.628781Z", - "iopub.status.busy": "2023-08-21T02:28:57.628673Z", - "iopub.status.idle": "2023-08-21T02:28:57.631185Z", - "shell.execute_reply": "2023-08-21T02:28:57.630909Z" + "iopub.execute_input": "2023-08-22T06:59:35.551288Z", + "iopub.status.busy": "2023-08-22T06:59:35.551134Z", + "iopub.status.idle": "2023-08-22T06:59:35.553370Z", + "shell.execute_reply": "2023-08-22T06:59:35.553102Z" }, "lines_to_next_cell": 0 }, @@ -2507,10 +2507,10 @@ "id": "0790f26e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.632749Z", - "iopub.status.busy": "2023-08-21T02:28:57.632622Z", - "iopub.status.idle": "2023-08-21T02:28:57.635950Z", - "shell.execute_reply": "2023-08-21T02:28:57.635645Z" + "iopub.execute_input": "2023-08-22T06:59:35.554980Z", + "iopub.status.busy": "2023-08-22T06:59:35.554846Z", + "iopub.status.idle": "2023-08-22T06:59:35.557806Z", + "shell.execute_reply": "2023-08-22T06:59:35.557573Z" }, "lines_to_next_cell": 2 }, @@ -2546,10 +2546,10 @@ "id": "4a8cf0ce", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.637431Z", - "iopub.status.busy": "2023-08-21T02:28:57.637345Z", - "iopub.status.idle": "2023-08-21T02:28:57.640679Z", - "shell.execute_reply": "2023-08-21T02:28:57.640387Z" + "iopub.execute_input": "2023-08-22T06:59:35.559235Z", + "iopub.status.busy": "2023-08-22T06:59:35.559122Z", + "iopub.status.idle": "2023-08-22T06:59:35.562452Z", + "shell.execute_reply": "2023-08-22T06:59:35.562071Z" }, "lines_to_next_cell": 0 }, @@ -2586,10 +2586,10 @@ "id": "94e7ff1a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.642306Z", - "iopub.status.busy": "2023-08-21T02:28:57.642190Z", - "iopub.status.idle": "2023-08-21T02:28:57.646804Z", - "shell.execute_reply": "2023-08-21T02:28:57.646534Z" + "iopub.execute_input": "2023-08-22T06:59:35.564237Z", + "iopub.status.busy": "2023-08-22T06:59:35.564138Z", + "iopub.status.idle": "2023-08-22T06:59:35.568635Z", + "shell.execute_reply": "2023-08-22T06:59:35.568359Z" } }, "outputs": [ @@ -2671,10 +2671,10 @@ "id": "137e23aa", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.648357Z", - "iopub.status.busy": "2023-08-21T02:28:57.648246Z", - "iopub.status.idle": "2023-08-21T02:28:57.651178Z", - "shell.execute_reply": "2023-08-21T02:28:57.650935Z" + "iopub.execute_input": "2023-08-22T06:59:35.570127Z", + "iopub.status.busy": "2023-08-22T06:59:35.570011Z", + "iopub.status.idle": "2023-08-22T06:59:35.573407Z", + "shell.execute_reply": "2023-08-22T06:59:35.573097Z" }, "lines_to_next_cell": 2 }, @@ -2721,10 +2721,10 @@ "id": "142c5217", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.652781Z", - "iopub.status.busy": "2023-08-21T02:28:57.652676Z", - "iopub.status.idle": "2023-08-21T02:28:57.665013Z", - "shell.execute_reply": "2023-08-21T02:28:57.664742Z" + "iopub.execute_input": "2023-08-22T06:59:35.575043Z", + "iopub.status.busy": "2023-08-22T06:59:35.574949Z", + "iopub.status.idle": "2023-08-22T06:59:35.585246Z", + "shell.execute_reply": "2023-08-22T06:59:35.584962Z" } }, "outputs": [ @@ -2809,10 +2809,10 @@ "id": "f5a272ee", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.666910Z", - "iopub.status.busy": "2023-08-21T02:28:57.666782Z", - "iopub.status.idle": "2023-08-21T02:28:57.669498Z", - "shell.execute_reply": "2023-08-21T02:28:57.669179Z" + "iopub.execute_input": "2023-08-22T06:59:35.587100Z", + "iopub.status.busy": "2023-08-22T06:59:35.586985Z", + "iopub.status.idle": "2023-08-22T06:59:35.589510Z", + "shell.execute_reply": "2023-08-22T06:59:35.589151Z" } }, "outputs": [ @@ -2846,10 +2846,10 @@ "id": "95e206a8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.671045Z", - "iopub.status.busy": "2023-08-21T02:28:57.670939Z", - "iopub.status.idle": "2023-08-21T02:28:57.679000Z", - "shell.execute_reply": "2023-08-21T02:28:57.678715Z" + "iopub.execute_input": "2023-08-22T06:59:35.591165Z", + "iopub.status.busy": "2023-08-22T06:59:35.591045Z", + "iopub.status.idle": "2023-08-22T06:59:35.598648Z", + "shell.execute_reply": "2023-08-22T06:59:35.598383Z" }, "lines_to_next_cell": 0 }, @@ -2901,10 +2901,10 @@ "id": "422563b7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.680643Z", - "iopub.status.busy": "2023-08-21T02:28:57.680560Z", - "iopub.status.idle": "2023-08-21T02:28:57.698929Z", - "shell.execute_reply": "2023-08-21T02:28:57.698652Z" + "iopub.execute_input": "2023-08-22T06:59:35.600269Z", + "iopub.status.busy": "2023-08-22T06:59:35.600186Z", + "iopub.status.idle": "2023-08-22T06:59:35.616715Z", + "shell.execute_reply": "2023-08-22T06:59:35.616375Z" }, "lines_to_next_cell": 2 }, @@ -2945,10 +2945,10 @@ "id": "583c860c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.700534Z", - "iopub.status.busy": "2023-08-21T02:28:57.700406Z", - "iopub.status.idle": "2023-08-21T02:28:57.702790Z", - "shell.execute_reply": "2023-08-21T02:28:57.702539Z" + "iopub.execute_input": "2023-08-22T06:59:35.618509Z", + "iopub.status.busy": "2023-08-22T06:59:35.618392Z", + "iopub.status.idle": "2023-08-22T06:59:35.620427Z", + "shell.execute_reply": "2023-08-22T06:59:35.620213Z" }, "lines_to_next_cell": 2 }, @@ -2982,10 +2982,10 @@ "id": "19ee3bf2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.704427Z", - "iopub.status.busy": "2023-08-21T02:28:57.704308Z", - "iopub.status.idle": "2023-08-21T02:28:57.707107Z", - "shell.execute_reply": "2023-08-21T02:28:57.706716Z" + "iopub.execute_input": "2023-08-22T06:59:35.622075Z", + "iopub.status.busy": "2023-08-22T06:59:35.621970Z", + "iopub.status.idle": "2023-08-22T06:59:35.624662Z", + "shell.execute_reply": "2023-08-22T06:59:35.624306Z" } }, "outputs": [], @@ -3031,10 +3031,10 @@ "id": "fdc0e5f1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.708836Z", - "iopub.status.busy": "2023-08-21T02:28:57.708707Z", - "iopub.status.idle": "2023-08-21T02:28:57.710507Z", - "shell.execute_reply": "2023-08-21T02:28:57.710220Z" + "iopub.execute_input": "2023-08-22T06:59:35.626535Z", + "iopub.status.busy": "2023-08-22T06:59:35.626411Z", + "iopub.status.idle": "2023-08-22T06:59:35.628326Z", + "shell.execute_reply": "2023-08-22T06:59:35.628023Z" }, "lines_to_next_cell": 0 }, @@ -3070,10 +3070,10 @@ "id": "2bb9d48b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.712025Z", - "iopub.status.busy": "2023-08-21T02:28:57.711919Z", - "iopub.status.idle": "2023-08-21T02:28:57.717961Z", - "shell.execute_reply": "2023-08-21T02:28:57.717623Z" + "iopub.execute_input": "2023-08-22T06:59:35.630001Z", + "iopub.status.busy": "2023-08-22T06:59:35.629870Z", + "iopub.status.idle": "2023-08-22T06:59:35.636000Z", + "shell.execute_reply": "2023-08-22T06:59:35.635697Z" }, "lines_to_next_cell": 0 }, @@ -3098,10 +3098,10 @@ "id": "649b57b3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.719733Z", - "iopub.status.busy": "2023-08-21T02:28:57.719643Z", - "iopub.status.idle": "2023-08-21T02:28:57.725788Z", - "shell.execute_reply": "2023-08-21T02:28:57.725511Z" + "iopub.execute_input": "2023-08-22T06:59:35.637746Z", + "iopub.status.busy": "2023-08-22T06:59:35.637618Z", + "iopub.status.idle": "2023-08-22T06:59:35.643400Z", + "shell.execute_reply": "2023-08-22T06:59:35.643102Z" } }, "outputs": [ @@ -3154,10 +3154,10 @@ "id": "d0aafd5e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.727208Z", - "iopub.status.busy": "2023-08-21T02:28:57.727114Z", - "iopub.status.idle": "2023-08-21T02:28:57.730769Z", - "shell.execute_reply": "2023-08-21T02:28:57.730507Z" + "iopub.execute_input": "2023-08-22T06:59:35.644912Z", + "iopub.status.busy": "2023-08-22T06:59:35.644814Z", + "iopub.status.idle": "2023-08-22T06:59:35.648144Z", + "shell.execute_reply": "2023-08-22T06:59:35.647828Z" }, "lines_to_next_cell": 0 }, @@ -3189,10 +3189,10 @@ "id": "ad02fb42", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:57.732302Z", - "iopub.status.busy": "2023-08-21T02:28:57.732202Z", - "iopub.status.idle": "2023-08-21T02:28:58.059169Z", - "shell.execute_reply": "2023-08-21T02:28:58.058739Z" + "iopub.execute_input": "2023-08-22T06:59:35.649991Z", + "iopub.status.busy": "2023-08-22T06:59:35.649857Z", + "iopub.status.idle": "2023-08-22T06:59:35.851869Z", + "shell.execute_reply": "2023-08-22T06:59:35.850800Z" }, "lines_to_next_cell": 2 }, @@ -3242,10 +3242,10 @@ "id": "901f772e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.061293Z", - "iopub.status.busy": "2023-08-21T02:28:58.061165Z", - "iopub.status.idle": "2023-08-21T02:28:58.067519Z", - "shell.execute_reply": "2023-08-21T02:28:58.067152Z" + "iopub.execute_input": "2023-08-22T06:59:35.857360Z", + "iopub.status.busy": "2023-08-22T06:59:35.856994Z", + "iopub.status.idle": "2023-08-22T06:59:35.868149Z", + "shell.execute_reply": "2023-08-22T06:59:35.867281Z" } }, "outputs": [ @@ -3327,10 +3327,10 @@ "id": "684f8941", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.069340Z", - "iopub.status.busy": "2023-08-21T02:28:58.069223Z", - "iopub.status.idle": "2023-08-21T02:28:58.071737Z", - "shell.execute_reply": "2023-08-21T02:28:58.071247Z" + "iopub.execute_input": "2023-08-22T06:59:35.872302Z", + "iopub.status.busy": "2023-08-22T06:59:35.871992Z", + "iopub.status.idle": "2023-08-22T06:59:35.881501Z", + "shell.execute_reply": "2023-08-22T06:59:35.879490Z" }, "lines_to_next_cell": 2 }, @@ -3371,10 +3371,10 @@ "id": "4d984cf0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.073571Z", - "iopub.status.busy": "2023-08-21T02:28:58.073457Z", - "iopub.status.idle": "2023-08-21T02:28:58.146516Z", - "shell.execute_reply": "2023-08-21T02:28:58.146020Z" + "iopub.execute_input": "2023-08-22T06:59:35.885276Z", + "iopub.status.busy": "2023-08-22T06:59:35.884561Z", + "iopub.status.idle": "2023-08-22T06:59:36.032887Z", + "shell.execute_reply": "2023-08-22T06:59:36.032527Z" }, "lines_to_next_cell": 0 }, @@ -3438,10 +3438,10 @@ "id": "d24f4e50", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.148624Z", - "iopub.status.busy": "2023-08-21T02:28:58.148360Z", - "iopub.status.idle": "2023-08-21T02:28:58.773984Z", - "shell.execute_reply": "2023-08-21T02:28:58.773325Z" + "iopub.execute_input": "2023-08-22T06:59:36.035053Z", + "iopub.status.busy": "2023-08-22T06:59:36.034905Z", + "iopub.status.idle": "2023-08-22T06:59:36.559516Z", + "shell.execute_reply": "2023-08-22T06:59:36.557112Z" } }, "outputs": [ @@ -3535,10 +3535,10 @@ "id": "25152580", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.778052Z", - "iopub.status.busy": "2023-08-21T02:28:58.777754Z", - "iopub.status.idle": "2023-08-21T02:28:58.791505Z", - "shell.execute_reply": "2023-08-21T02:28:58.790362Z" + "iopub.execute_input": "2023-08-22T06:59:36.564551Z", + "iopub.status.busy": "2023-08-22T06:59:36.564196Z", + "iopub.status.idle": "2023-08-22T06:59:36.582460Z", + "shell.execute_reply": "2023-08-22T06:59:36.580635Z" } }, "outputs": [ @@ -3610,10 +3610,10 @@ "id": "b8ea6e08", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.798441Z", - "iopub.status.busy": "2023-08-21T02:28:58.798187Z", - "iopub.status.idle": "2023-08-21T02:28:58.805015Z", - "shell.execute_reply": "2023-08-21T02:28:58.804266Z" + "iopub.execute_input": "2023-08-22T06:59:36.590532Z", + "iopub.status.busy": "2023-08-22T06:59:36.590038Z", + "iopub.status.idle": "2023-08-22T06:59:36.605488Z", + "shell.execute_reply": "2023-08-22T06:59:36.602880Z" }, "lines_to_next_cell": 0 }, @@ -3650,10 +3650,10 @@ "id": "def80d79", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.808423Z", - "iopub.status.busy": "2023-08-21T02:28:58.807929Z", - "iopub.status.idle": "2023-08-21T02:28:58.826147Z", - "shell.execute_reply": "2023-08-21T02:28:58.825308Z" + "iopub.execute_input": "2023-08-22T06:59:36.610362Z", + "iopub.status.busy": "2023-08-22T06:59:36.609709Z", + "iopub.status.idle": "2023-08-22T06:59:36.624089Z", + "shell.execute_reply": "2023-08-22T06:59:36.623200Z" }, "lines_to_next_cell": 0 }, @@ -3676,10 +3676,10 @@ "id": "f899d5ab", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.838005Z", - "iopub.status.busy": "2023-08-21T02:28:58.837542Z", - "iopub.status.idle": "2023-08-21T02:28:58.842697Z", - "shell.execute_reply": "2023-08-21T02:28:58.841989Z" + "iopub.execute_input": "2023-08-22T06:59:36.630386Z", + "iopub.status.busy": "2023-08-22T06:59:36.629966Z", + "iopub.status.idle": "2023-08-22T06:59:36.636403Z", + "shell.execute_reply": "2023-08-22T06:59:36.635734Z" } }, "outputs": [ @@ -3718,10 +3718,10 @@ "id": "76f4cea5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.846154Z", - "iopub.status.busy": "2023-08-21T02:28:58.845860Z", - "iopub.status.idle": "2023-08-21T02:28:58.936368Z", - "shell.execute_reply": "2023-08-21T02:28:58.931496Z" + "iopub.execute_input": "2023-08-22T06:59:36.642541Z", + "iopub.status.busy": "2023-08-22T06:59:36.642195Z", + "iopub.status.idle": "2023-08-22T06:59:36.742213Z", + "shell.execute_reply": "2023-08-22T06:59:36.740543Z" } }, "outputs": [ @@ -4122,10 +4122,10 @@ "id": "5778ada8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.941746Z", - "iopub.status.busy": "2023-08-21T02:28:58.941366Z", - "iopub.status.idle": "2023-08-21T02:28:58.948890Z", - "shell.execute_reply": "2023-08-21T02:28:58.947630Z" + "iopub.execute_input": "2023-08-22T06:59:36.748318Z", + "iopub.status.busy": "2023-08-22T06:59:36.747980Z", + "iopub.status.idle": "2023-08-22T06:59:36.753044Z", + "shell.execute_reply": "2023-08-22T06:59:36.752001Z" }, "lines_to_next_cell": 0 }, @@ -4149,10 +4149,10 @@ "id": "c6da14b9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:58.953721Z", - "iopub.status.busy": "2023-08-21T02:28:58.953330Z", - "iopub.status.idle": "2023-08-21T02:28:59.054283Z", - "shell.execute_reply": "2023-08-21T02:28:59.053564Z" + "iopub.execute_input": "2023-08-22T06:59:36.761294Z", + "iopub.status.busy": "2023-08-22T06:59:36.760741Z", + "iopub.status.idle": "2023-08-22T06:59:36.824675Z", + "shell.execute_reply": "2023-08-22T06:59:36.823419Z" } }, "outputs": [ @@ -4559,10 +4559,10 @@ "id": "461d57c5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.063565Z", - "iopub.status.busy": "2023-08-21T02:28:59.063233Z", - "iopub.status.idle": "2023-08-21T02:28:59.071787Z", - "shell.execute_reply": "2023-08-21T02:28:59.070620Z" + "iopub.execute_input": "2023-08-22T06:59:36.832613Z", + "iopub.status.busy": "2023-08-22T06:59:36.831243Z", + "iopub.status.idle": "2023-08-22T06:59:36.839557Z", + "shell.execute_reply": "2023-08-22T06:59:36.838190Z" } }, "outputs": [ @@ -4596,10 +4596,10 @@ "id": "05d33247", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.077767Z", - "iopub.status.busy": "2023-08-21T02:28:59.077090Z", - "iopub.status.idle": "2023-08-21T02:28:59.085265Z", - "shell.execute_reply": "2023-08-21T02:28:59.084291Z" + "iopub.execute_input": "2023-08-22T06:59:36.846635Z", + "iopub.status.busy": "2023-08-22T06:59:36.846336Z", + "iopub.status.idle": "2023-08-22T06:59:36.854114Z", + "shell.execute_reply": "2023-08-22T06:59:36.853108Z" }, "lines_to_next_cell": 2 }, @@ -4639,10 +4639,10 @@ "id": "bee42b38", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.089190Z", - "iopub.status.busy": "2023-08-21T02:28:59.088696Z", - "iopub.status.idle": "2023-08-21T02:28:59.099445Z", - "shell.execute_reply": "2023-08-21T02:28:59.098750Z" + "iopub.execute_input": "2023-08-22T06:59:36.861230Z", + "iopub.status.busy": "2023-08-22T06:59:36.860269Z", + "iopub.status.idle": "2023-08-22T06:59:36.869236Z", + "shell.execute_reply": "2023-08-22T06:59:36.868250Z" }, "lines_to_next_cell": 0 }, @@ -4688,10 +4688,10 @@ "id": "4aa60857", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.103423Z", - "iopub.status.busy": "2023-08-21T02:28:59.103057Z", - "iopub.status.idle": "2023-08-21T02:28:59.112346Z", - "shell.execute_reply": "2023-08-21T02:28:59.111002Z" + "iopub.execute_input": "2023-08-22T06:59:36.876998Z", + "iopub.status.busy": "2023-08-22T06:59:36.876016Z", + "iopub.status.idle": "2023-08-22T06:59:36.883621Z", + "shell.execute_reply": "2023-08-22T06:59:36.882372Z" }, "lines_to_next_cell": 0 }, @@ -4745,10 +4745,10 @@ "id": "894d3e2c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.116495Z", - "iopub.status.busy": "2023-08-21T02:28:59.116193Z", - "iopub.status.idle": "2023-08-21T02:28:59.250351Z", - "shell.execute_reply": "2023-08-21T02:28:59.249608Z" + "iopub.execute_input": "2023-08-22T06:59:36.889441Z", + "iopub.status.busy": "2023-08-22T06:59:36.888780Z", + "iopub.status.idle": "2023-08-22T06:59:37.004601Z", + "shell.execute_reply": "2023-08-22T06:59:37.003102Z" } }, "outputs": [ @@ -4787,10 +4787,10 @@ "id": "d636746e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.253708Z", - "iopub.status.busy": "2023-08-21T02:28:59.253326Z", - "iopub.status.idle": "2023-08-21T02:28:59.260644Z", - "shell.execute_reply": "2023-08-21T02:28:59.259501Z" + "iopub.execute_input": "2023-08-22T06:59:37.014352Z", + "iopub.status.busy": "2023-08-22T06:59:37.013713Z", + "iopub.status.idle": "2023-08-22T06:59:37.022133Z", + "shell.execute_reply": "2023-08-22T06:59:37.021189Z" } }, "outputs": [], @@ -4816,10 +4816,10 @@ "id": "ce6a1623", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.264364Z", - "iopub.status.busy": "2023-08-21T02:28:59.264112Z", - "iopub.status.idle": "2023-08-21T02:28:59.384102Z", - "shell.execute_reply": "2023-08-21T02:28:59.383714Z" + "iopub.execute_input": "2023-08-22T06:59:37.030881Z", + "iopub.status.busy": "2023-08-22T06:59:37.030334Z", + "iopub.status.idle": "2023-08-22T06:59:37.126992Z", + "shell.execute_reply": "2023-08-22T06:59:37.126566Z" } }, "outputs": [ @@ -4862,10 +4862,10 @@ "id": "9fb8b759", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.386009Z", - "iopub.status.busy": "2023-08-21T02:28:59.385867Z", - "iopub.status.idle": "2023-08-21T02:28:59.478822Z", - "shell.execute_reply": "2023-08-21T02:28:59.477841Z" + "iopub.execute_input": "2023-08-22T06:59:37.128893Z", + "iopub.status.busy": "2023-08-22T06:59:37.128737Z", + "iopub.status.idle": "2023-08-22T06:59:37.220758Z", + "shell.execute_reply": "2023-08-22T06:59:37.219419Z" } }, "outputs": [], @@ -4887,10 +4887,10 @@ "id": "ee272341", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.482988Z", - "iopub.status.busy": "2023-08-21T02:28:59.482517Z", - "iopub.status.idle": "2023-08-21T02:28:59.506926Z", - "shell.execute_reply": "2023-08-21T02:28:59.506267Z" + "iopub.execute_input": "2023-08-22T06:59:37.227931Z", + "iopub.status.busy": "2023-08-22T06:59:37.227304Z", + "iopub.status.idle": "2023-08-22T06:59:37.252847Z", + "shell.execute_reply": "2023-08-22T06:59:37.251756Z" }, "lines_to_next_cell": 0 }, @@ -4921,10 +4921,10 @@ "id": "1f5bde07", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.510834Z", - "iopub.status.busy": "2023-08-21T02:28:59.510470Z", - "iopub.status.idle": "2023-08-21T02:28:59.792175Z", - "shell.execute_reply": "2023-08-21T02:28:59.791845Z" + "iopub.execute_input": "2023-08-22T06:59:37.263402Z", + "iopub.status.busy": "2023-08-22T06:59:37.262273Z", + "iopub.status.idle": "2023-08-22T06:59:37.482693Z", + "shell.execute_reply": "2023-08-22T06:59:37.479472Z" }, "lines_to_next_cell": 0 }, @@ -4933,7 +4933,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_80940/3779905754.py:8: UserWarning: FixedFormatter should only be used together with FixedLocator\n", + "/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_84444/3779905754.py:8: UserWarning: FixedFormatter should only be used together with FixedLocator\n", " ax_hr.set_xticklabels(range(24)[::2], fontsize=20)\n" ] }, @@ -4978,10 +4978,10 @@ "id": "b0bd66a1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:28:59.793823Z", - "iopub.status.busy": "2023-08-21T02:28:59.793732Z", - "iopub.status.idle": "2023-08-21T02:28:59.904438Z", - "shell.execute_reply": "2023-08-21T02:28:59.904151Z" + "iopub.execute_input": "2023-08-22T06:59:37.487973Z", + "iopub.status.busy": "2023-08-22T06:59:37.486725Z", + "iopub.status.idle": "2023-08-22T06:59:37.588898Z", + "shell.execute_reply": "2023-08-22T06:59:37.588557Z" } }, "outputs": [ @@ -5031,7 +5031,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -5044,7 +5044,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch05-resample-lab.Rmd b/Ch05-resample-lab.Rmd index 34e2d1d..1733c87 100644 --- a/Ch05-resample-lab.Rmd +++ b/Ch05-resample-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch05-resample-lab.ipynb b/Ch05-resample-lab.ipynb index 85c1f65..2314c64 100644 --- a/Ch05-resample-lab.ipynb +++ b/Ch05-resample-lab.ipynb @@ -29,10 +29,10 @@ "id": "e7712cfe", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:01.252458Z", - "iopub.status.busy": "2023-08-21T02:29:01.251970Z", - "iopub.status.idle": "2023-08-21T02:29:02.044045Z", - "shell.execute_reply": "2023-08-21T02:29:02.043730Z" + "iopub.execute_input": "2023-08-22T06:59:40.827828Z", + "iopub.status.busy": "2023-08-22T06:59:40.827725Z", + "iopub.status.idle": "2023-08-22T06:59:41.658013Z", + "shell.execute_reply": "2023-08-22T06:59:41.657645Z" }, "lines_to_next_cell": 2 }, @@ -61,10 +61,10 @@ "id": "21c2ed4f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.045927Z", - "iopub.status.busy": "2023-08-21T02:29:02.045761Z", - "iopub.status.idle": "2023-08-21T02:29:02.047761Z", - "shell.execute_reply": "2023-08-21T02:29:02.047491Z" + "iopub.execute_input": "2023-08-22T06:59:41.659951Z", + "iopub.status.busy": "2023-08-22T06:59:41.659798Z", + "iopub.status.idle": "2023-08-22T06:59:41.661744Z", + "shell.execute_reply": "2023-08-22T06:59:41.661437Z" }, "lines_to_next_cell": 2 }, @@ -105,10 +105,10 @@ "id": "8af59641", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.049239Z", - "iopub.status.busy": "2023-08-21T02:29:02.049145Z", - "iopub.status.idle": "2023-08-21T02:29:02.055524Z", - "shell.execute_reply": "2023-08-21T02:29:02.055162Z" + "iopub.execute_input": "2023-08-22T06:59:41.663216Z", + "iopub.status.busy": "2023-08-22T06:59:41.663117Z", + "iopub.status.idle": "2023-08-22T06:59:41.667680Z", + "shell.execute_reply": "2023-08-22T06:59:41.667343Z" } }, "outputs": [], @@ -133,10 +133,10 @@ "id": "d9b0b7c8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.057278Z", - "iopub.status.busy": "2023-08-21T02:29:02.057182Z", - "iopub.status.idle": "2023-08-21T02:29:02.062537Z", - "shell.execute_reply": "2023-08-21T02:29:02.062265Z" + "iopub.execute_input": "2023-08-22T06:59:41.669501Z", + "iopub.status.busy": "2023-08-22T06:59:41.669395Z", + "iopub.status.idle": "2023-08-22T06:59:41.674461Z", + "shell.execute_reply": "2023-08-22T06:59:41.674176Z" } }, "outputs": [], @@ -163,10 +163,10 @@ "id": "3e77d831", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.064056Z", - "iopub.status.busy": "2023-08-21T02:29:02.063966Z", - "iopub.status.idle": "2023-08-21T02:29:02.068279Z", - "shell.execute_reply": "2023-08-21T02:29:02.068024Z" + "iopub.execute_input": "2023-08-22T06:59:41.676257Z", + "iopub.status.busy": "2023-08-22T06:59:41.676134Z", + "iopub.status.idle": "2023-08-22T06:59:41.680728Z", + "shell.execute_reply": "2023-08-22T06:59:41.680456Z" } }, "outputs": [ @@ -207,10 +207,10 @@ "id": "0aa4bfcc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.069789Z", - "iopub.status.busy": "2023-08-21T02:29:02.069682Z", - "iopub.status.idle": "2023-08-21T02:29:02.071953Z", - "shell.execute_reply": "2023-08-21T02:29:02.071703Z" + "iopub.execute_input": "2023-08-22T06:59:41.682418Z", + "iopub.status.busy": "2023-08-22T06:59:41.682304Z", + "iopub.status.idle": "2023-08-22T06:59:41.684531Z", + "shell.execute_reply": "2023-08-22T06:59:41.684276Z" } }, "outputs": [], @@ -250,10 +250,10 @@ "id": "a0dbd55f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.073322Z", - "iopub.status.busy": "2023-08-21T02:29:02.073229Z", - "iopub.status.idle": "2023-08-21T02:29:02.088464Z", - "shell.execute_reply": "2023-08-21T02:29:02.088192Z" + "iopub.execute_input": "2023-08-22T06:59:41.686084Z", + "iopub.status.busy": "2023-08-22T06:59:41.685977Z", + "iopub.status.idle": "2023-08-22T06:59:41.701551Z", + "shell.execute_reply": "2023-08-22T06:59:41.701265Z" } }, "outputs": [ @@ -294,10 +294,10 @@ "id": "885136a4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.089889Z", - "iopub.status.busy": "2023-08-21T02:29:02.089804Z", - "iopub.status.idle": "2023-08-21T02:29:02.105353Z", - "shell.execute_reply": "2023-08-21T02:29:02.105089Z" + "iopub.execute_input": "2023-08-22T06:59:41.703198Z", + "iopub.status.busy": "2023-08-22T06:59:41.703080Z", + "iopub.status.idle": "2023-08-22T06:59:41.719142Z", + "shell.execute_reply": "2023-08-22T06:59:41.718778Z" } }, "outputs": [ @@ -377,10 +377,10 @@ "id": "6d957d8c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:02.106979Z", - "iopub.status.busy": "2023-08-21T02:29:02.106884Z", - "iopub.status.idle": "2023-08-21T02:29:03.184550Z", - "shell.execute_reply": "2023-08-21T02:29:03.184259Z" + "iopub.execute_input": "2023-08-22T06:59:41.721067Z", + "iopub.status.busy": "2023-08-22T06:59:41.720935Z", + "iopub.status.idle": "2023-08-22T06:59:42.841536Z", + "shell.execute_reply": "2023-08-22T06:59:42.841242Z" }, "lines_to_next_cell": 0 }, @@ -445,10 +445,10 @@ "id": "e2b5ce95", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.186226Z", - "iopub.status.busy": "2023-08-21T02:29:03.186108Z", - "iopub.status.idle": "2023-08-21T02:29:03.782413Z", - "shell.execute_reply": "2023-08-21T02:29:03.782122Z" + "iopub.execute_input": "2023-08-22T06:59:42.843438Z", + "iopub.status.busy": "2023-08-22T06:59:42.843308Z", + "iopub.status.idle": "2023-08-22T06:59:43.408832Z", + "shell.execute_reply": "2023-08-22T06:59:43.408347Z" }, "lines_to_next_cell": 0 }, @@ -502,10 +502,10 @@ "id": "1dda1bd7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.783997Z", - "iopub.status.busy": "2023-08-21T02:29:03.783886Z", - "iopub.status.idle": "2023-08-21T02:29:03.786132Z", - "shell.execute_reply": "2023-08-21T02:29:03.785881Z" + "iopub.execute_input": "2023-08-22T06:59:43.411083Z", + "iopub.status.busy": "2023-08-22T06:59:43.410940Z", + "iopub.status.idle": "2023-08-22T06:59:43.413889Z", + "shell.execute_reply": "2023-08-22T06:59:43.413456Z" } }, "outputs": [ @@ -544,10 +544,10 @@ "id": "fb25fa70", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.787622Z", - "iopub.status.busy": "2023-08-21T02:29:03.787525Z", - "iopub.status.idle": "2023-08-21T02:29:03.809671Z", - "shell.execute_reply": "2023-08-21T02:29:03.809398Z" + "iopub.execute_input": "2023-08-22T06:59:43.415865Z", + "iopub.status.busy": "2023-08-22T06:59:43.415724Z", + "iopub.status.idle": "2023-08-22T06:59:43.437716Z", + "shell.execute_reply": "2023-08-22T06:59:43.437344Z" }, "lines_to_next_cell": 0 }, @@ -609,10 +609,10 @@ "id": "d78795cd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.811123Z", - "iopub.status.busy": "2023-08-21T02:29:03.811046Z", - "iopub.status.idle": "2023-08-21T02:29:03.817840Z", - "shell.execute_reply": "2023-08-21T02:29:03.817582Z" + "iopub.execute_input": "2023-08-22T06:59:43.439940Z", + "iopub.status.busy": "2023-08-22T06:59:43.439783Z", + "iopub.status.idle": "2023-08-22T06:59:43.447580Z", + "shell.execute_reply": "2023-08-22T06:59:43.447286Z" }, "lines_to_next_cell": 2 }, @@ -653,10 +653,10 @@ "id": "0407ad56", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.819308Z", - "iopub.status.busy": "2023-08-21T02:29:03.819228Z", - "iopub.status.idle": "2023-08-21T02:29:03.851921Z", - "shell.execute_reply": "2023-08-21T02:29:03.851658Z" + "iopub.execute_input": "2023-08-22T06:59:43.449591Z", + "iopub.status.busy": "2023-08-22T06:59:43.449452Z", + "iopub.status.idle": "2023-08-22T06:59:43.483638Z", + "shell.execute_reply": "2023-08-22T06:59:43.483222Z" } }, "outputs": [ @@ -727,10 +727,10 @@ "id": "f04f15bd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.853415Z", - "iopub.status.busy": "2023-08-21T02:29:03.853334Z", - "iopub.status.idle": "2023-08-21T02:29:03.857370Z", - "shell.execute_reply": "2023-08-21T02:29:03.857115Z" + "iopub.execute_input": "2023-08-22T06:59:43.485600Z", + "iopub.status.busy": "2023-08-22T06:59:43.485469Z", + "iopub.status.idle": "2023-08-22T06:59:43.488993Z", + "shell.execute_reply": "2023-08-22T06:59:43.488698Z" }, "lines_to_next_cell": 0 }, @@ -761,10 +761,10 @@ "id": "f98c0323", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.858828Z", - "iopub.status.busy": "2023-08-21T02:29:03.858753Z", - "iopub.status.idle": "2023-08-21T02:29:03.861443Z", - "shell.execute_reply": "2023-08-21T02:29:03.861198Z" + "iopub.execute_input": "2023-08-22T06:59:43.490952Z", + "iopub.status.busy": "2023-08-22T06:59:43.490857Z", + "iopub.status.idle": "2023-08-22T06:59:43.494027Z", + "shell.execute_reply": "2023-08-22T06:59:43.493695Z" } }, "outputs": [ @@ -800,10 +800,10 @@ "id": "bcd40175", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.862933Z", - "iopub.status.busy": "2023-08-21T02:29:03.862830Z", - "iopub.status.idle": "2023-08-21T02:29:03.865766Z", - "shell.execute_reply": "2023-08-21T02:29:03.865514Z" + "iopub.execute_input": "2023-08-22T06:59:43.495852Z", + "iopub.status.busy": "2023-08-22T06:59:43.495690Z", + "iopub.status.idle": "2023-08-22T06:59:43.498806Z", + "shell.execute_reply": "2023-08-22T06:59:43.498500Z" }, "lines_to_next_cell": 2 }, @@ -843,10 +843,10 @@ "id": "ab6602cd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.867170Z", - "iopub.status.busy": "2023-08-21T02:29:03.867072Z", - "iopub.status.idle": "2023-08-21T02:29:03.869326Z", - "shell.execute_reply": "2023-08-21T02:29:03.869094Z" + "iopub.execute_input": "2023-08-22T06:59:43.500527Z", + "iopub.status.busy": "2023-08-22T06:59:43.500424Z", + "iopub.status.idle": "2023-08-22T06:59:43.502886Z", + "shell.execute_reply": "2023-08-22T06:59:43.502621Z" }, "lines_to_next_cell": 0 }, @@ -888,10 +888,10 @@ "id": "4a323513", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:03.870755Z", - "iopub.status.busy": "2023-08-21T02:29:03.870664Z", - "iopub.status.idle": "2023-08-21T02:29:04.157907Z", - "shell.execute_reply": "2023-08-21T02:29:04.157623Z" + "iopub.execute_input": "2023-08-22T06:59:43.504576Z", + "iopub.status.busy": "2023-08-22T06:59:43.504471Z", + "iopub.status.idle": "2023-08-22T06:59:43.776972Z", + "shell.execute_reply": "2023-08-22T06:59:43.776638Z" } }, "outputs": [ @@ -954,10 +954,10 @@ "id": "0220f3af", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:04.159500Z", - "iopub.status.busy": "2023-08-21T02:29:04.159419Z", - "iopub.status.idle": "2023-08-21T02:29:04.161332Z", - "shell.execute_reply": "2023-08-21T02:29:04.161073Z" + "iopub.execute_input": "2023-08-22T06:59:43.778737Z", + "iopub.status.busy": "2023-08-22T06:59:43.778622Z", + "iopub.status.idle": "2023-08-22T06:59:43.780660Z", + "shell.execute_reply": "2023-08-22T06:59:43.780373Z" }, "lines_to_next_cell": 0 }, @@ -989,10 +989,10 @@ "id": "62037dcb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:04.162950Z", - "iopub.status.busy": "2023-08-21T02:29:04.162849Z", - "iopub.status.idle": "2023-08-21T02:29:04.164486Z", - "shell.execute_reply": "2023-08-21T02:29:04.164241Z" + "iopub.execute_input": "2023-08-22T06:59:43.782304Z", + "iopub.status.busy": "2023-08-22T06:59:43.782178Z", + "iopub.status.idle": "2023-08-22T06:59:43.783926Z", + "shell.execute_reply": "2023-08-22T06:59:43.783681Z" }, "lines_to_next_cell": 0 }, @@ -1022,10 +1022,10 @@ "id": "b8bdb7a4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:04.165879Z", - "iopub.status.busy": "2023-08-21T02:29:04.165798Z", - "iopub.status.idle": "2023-08-21T02:29:04.194029Z", - "shell.execute_reply": "2023-08-21T02:29:04.193764Z" + "iopub.execute_input": "2023-08-22T06:59:43.785584Z", + "iopub.status.busy": "2023-08-22T06:59:43.785479Z", + "iopub.status.idle": "2023-08-22T06:59:43.814180Z", + "shell.execute_reply": "2023-08-22T06:59:43.813871Z" }, "lines_to_next_cell": 0 }, @@ -1073,10 +1073,10 @@ "id": "36808258", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:04.195612Z", - "iopub.status.busy": "2023-08-21T02:29:04.195529Z", - "iopub.status.idle": "2023-08-21T02:29:06.747175Z", - "shell.execute_reply": "2023-08-21T02:29:06.746638Z" + "iopub.execute_input": "2023-08-22T06:59:43.815884Z", + "iopub.status.busy": "2023-08-22T06:59:43.815750Z", + "iopub.status.idle": "2023-08-22T06:59:46.317022Z", + "shell.execute_reply": "2023-08-22T06:59:46.316748Z" }, "lines_to_next_cell": 2 }, @@ -1123,10 +1123,10 @@ "id": "c9aea297", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:06.749614Z", - "iopub.status.busy": "2023-08-21T02:29:06.749433Z", - "iopub.status.idle": "2023-08-21T02:29:06.812583Z", - "shell.execute_reply": "2023-08-21T02:29:06.812298Z" + "iopub.execute_input": "2023-08-22T06:59:46.318852Z", + "iopub.status.busy": "2023-08-22T06:59:46.318744Z", + "iopub.status.idle": "2023-08-22T06:59:46.401268Z", + "shell.execute_reply": "2023-08-22T06:59:46.400928Z" }, "lines_to_next_cell": 2 }, @@ -1195,10 +1195,10 @@ "id": "79c56529", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:06.814267Z", - "iopub.status.busy": "2023-08-21T02:29:06.814125Z", - "iopub.status.idle": "2023-08-21T02:29:10.162177Z", - "shell.execute_reply": "2023-08-21T02:29:10.161855Z" + "iopub.execute_input": "2023-08-22T06:59:46.403009Z", + "iopub.status.busy": "2023-08-22T06:59:46.402852Z", + "iopub.status.idle": "2023-08-22T06:59:50.039894Z", + "shell.execute_reply": "2023-08-22T06:59:50.039566Z" } }, "outputs": [ @@ -1238,10 +1238,10 @@ "id": "4d0b4edc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:10.163852Z", - "iopub.status.busy": "2023-08-21T02:29:10.163742Z", - "iopub.status.idle": "2023-08-21T02:29:10.173834Z", - "shell.execute_reply": "2023-08-21T02:29:10.173578Z" + "iopub.execute_input": "2023-08-22T06:59:50.041629Z", + "iopub.status.busy": "2023-08-22T06:59:50.041514Z", + "iopub.status.idle": "2023-08-22T06:59:50.052046Z", + "shell.execute_reply": "2023-08-22T06:59:50.051690Z" }, "lines_to_next_cell": 0 }, @@ -1279,7 +1279,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -1292,7 +1292,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch06-varselect-lab.Rmd b/Ch06-varselect-lab.Rmd index 9396072..4979e46 100644 --- a/Ch06-varselect-lab.Rmd +++ b/Ch06-varselect-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch06-varselect-lab.ipynb b/Ch06-varselect-lab.ipynb index f3342ea..94ddd1b 100644 --- a/Ch06-varselect-lab.ipynb +++ b/Ch06-varselect-lab.ipynb @@ -26,10 +26,10 @@ "id": "638bdae9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:11.258581Z", - "iopub.status.busy": "2023-08-21T02:29:11.258299Z", - "iopub.status.idle": "2023-08-21T02:29:12.282137Z", - "shell.execute_reply": "2023-08-21T02:29:12.281824Z" + "iopub.execute_input": "2023-08-22T06:59:53.093245Z", + "iopub.status.busy": "2023-08-22T06:59:53.093143Z", + "iopub.status.idle": "2023-08-22T06:59:54.054493Z", + "shell.execute_reply": "2023-08-22T06:59:54.054110Z" } }, "outputs": [], @@ -61,10 +61,10 @@ "id": "c4b3398b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:12.284057Z", - "iopub.status.busy": "2023-08-21T02:29:12.283895Z", - "iopub.status.idle": "2023-08-21T02:29:14.091024Z", - "shell.execute_reply": "2023-08-21T02:29:14.090709Z" + "iopub.execute_input": "2023-08-22T06:59:54.056594Z", + "iopub.status.busy": "2023-08-22T06:59:54.056412Z", + "iopub.status.idle": "2023-08-22T06:59:56.004484Z", + "shell.execute_reply": "2023-08-22T06:59:56.004082Z" }, "lines_to_next_cell": 0 }, @@ -73,11 +73,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "Requirement already satisfied: l0bnb in /Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages (1.0.0)\r\n", - "Requirement already satisfied: numpy>=1.18.1 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages (from l0bnb) (1.24.2)\r\n", - "Requirement already satisfied: scipy>=1.4.1 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages (from l0bnb) (1.11.1)\r\n", - "Requirement already satisfied: numba>=0.53.1 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages (from l0bnb) (0.57.1)\r\n", - "Requirement already satisfied: llvmlite<0.41,>=0.40.0dev0 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages (from numba>=0.53.1->l0bnb) (0.40.1)\r\n" + "Requirement already satisfied: l0bnb in /Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages (1.0.0)\r\n", + "Requirement already satisfied: numpy>=1.18.1 in /Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages (from l0bnb) (1.24.2)\r\n", + "Requirement already satisfied: scipy>=1.4.1 in /Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages (from l0bnb) (1.11.1)\r\n", + "Requirement already satisfied: numba>=0.53.1 in /Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages (from l0bnb) (0.57.1)\r\n", + "Requirement already satisfied: llvmlite<0.41,>=0.40.0dev0 in /Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages (from numba>=0.53.1->l0bnb) (0.40.1)\r\n" ] } ], @@ -125,10 +125,10 @@ "id": "18d03122", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.092873Z", - "iopub.status.busy": "2023-08-21T02:29:14.092763Z", - "iopub.status.idle": "2023-08-21T02:29:14.099984Z", - "shell.execute_reply": "2023-08-21T02:29:14.099726Z" + "iopub.execute_input": "2023-08-22T06:59:56.006401Z", + "iopub.status.busy": "2023-08-22T06:59:56.006276Z", + "iopub.status.idle": "2023-08-22T06:59:56.013280Z", + "shell.execute_reply": "2023-08-22T06:59:56.012957Z" } }, "outputs": [ @@ -164,10 +164,10 @@ "id": "87a4ba00", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.101494Z", - "iopub.status.busy": "2023-08-21T02:29:14.101409Z", - "iopub.status.idle": "2023-08-21T02:29:14.104265Z", - "shell.execute_reply": "2023-08-21T02:29:14.104009Z" + "iopub.execute_input": "2023-08-22T06:59:56.014992Z", + "iopub.status.busy": "2023-08-22T06:59:56.014883Z", + "iopub.status.idle": "2023-08-22T06:59:56.017852Z", + "shell.execute_reply": "2023-08-22T06:59:56.017594Z" }, "lines_to_next_cell": 2 }, @@ -205,10 +205,10 @@ "id": "97d6b69c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.105644Z", - "iopub.status.busy": "2023-08-21T02:29:14.105549Z", - "iopub.status.idle": "2023-08-21T02:29:14.107583Z", - "shell.execute_reply": "2023-08-21T02:29:14.107310Z" + "iopub.execute_input": "2023-08-22T06:59:56.019330Z", + "iopub.status.busy": "2023-08-22T06:59:56.019227Z", + "iopub.status.idle": "2023-08-22T06:59:56.021261Z", + "shell.execute_reply": "2023-08-22T06:59:56.020923Z" }, "lines_to_next_cell": 0 }, @@ -237,10 +237,10 @@ "id": "2575e116", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.109006Z", - "iopub.status.busy": "2023-08-21T02:29:14.108924Z", - "iopub.status.idle": "2023-08-21T02:29:14.129547Z", - "shell.execute_reply": "2023-08-21T02:29:14.129253Z" + "iopub.execute_input": "2023-08-22T06:59:56.023126Z", + "iopub.status.busy": "2023-08-22T06:59:56.023002Z", + "iopub.status.idle": "2023-08-22T06:59:56.043909Z", + "shell.execute_reply": "2023-08-22T06:59:56.043598Z" } }, "outputs": [], @@ -265,10 +265,10 @@ "id": "4cfae1c0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.131136Z", - "iopub.status.busy": "2023-08-21T02:29:14.131050Z", - "iopub.status.idle": "2023-08-21T02:29:14.132859Z", - "shell.execute_reply": "2023-08-21T02:29:14.132610Z" + "iopub.execute_input": "2023-08-22T06:59:56.046001Z", + "iopub.status.busy": "2023-08-22T06:59:56.045882Z", + "iopub.status.idle": "2023-08-22T06:59:56.047752Z", + "shell.execute_reply": "2023-08-22T06:59:56.047459Z" }, "lines_to_next_cell": 0 }, @@ -303,10 +303,10 @@ "id": "98b62676", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.134396Z", - "iopub.status.busy": "2023-08-21T02:29:14.134312Z", - "iopub.status.idle": "2023-08-21T02:29:14.136156Z", - "shell.execute_reply": "2023-08-21T02:29:14.135905Z" + "iopub.execute_input": "2023-08-22T06:59:56.049394Z", + "iopub.status.busy": "2023-08-22T06:59:56.049284Z", + "iopub.status.idle": "2023-08-22T06:59:56.051180Z", + "shell.execute_reply": "2023-08-22T06:59:56.050841Z" } }, "outputs": [], @@ -334,10 +334,10 @@ "id": "3d1bd25a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:14.137540Z", - "iopub.status.busy": "2023-08-21T02:29:14.137462Z", - "iopub.status.idle": "2023-08-21T02:29:15.145790Z", - "shell.execute_reply": "2023-08-21T02:29:15.145505Z" + "iopub.execute_input": "2023-08-22T06:59:56.053484Z", + "iopub.status.busy": "2023-08-22T06:59:56.053197Z", + "iopub.status.idle": "2023-08-22T06:59:57.116576Z", + "shell.execute_reply": "2023-08-22T06:59:57.116202Z" } }, "outputs": [ @@ -391,10 +391,10 @@ "id": "b25dfa6c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:15.147492Z", - "iopub.status.busy": "2023-08-21T02:29:15.147368Z", - "iopub.status.idle": "2023-08-21T02:29:15.796510Z", - "shell.execute_reply": "2023-08-21T02:29:15.796218Z" + "iopub.execute_input": "2023-08-22T06:59:57.118521Z", + "iopub.status.busy": "2023-08-22T06:59:57.118381Z", + "iopub.status.idle": "2023-08-22T06:59:57.757333Z", + "shell.execute_reply": "2023-08-22T06:59:57.756933Z" } }, "outputs": [ @@ -457,10 +457,10 @@ "id": "0ef3f82d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:15.798342Z", - "iopub.status.busy": "2023-08-21T02:29:15.798201Z", - "iopub.status.idle": "2023-08-21T02:29:15.800265Z", - "shell.execute_reply": "2023-08-21T02:29:15.799952Z" + "iopub.execute_input": "2023-08-22T06:59:57.759379Z", + "iopub.status.busy": "2023-08-22T06:59:57.759234Z", + "iopub.status.idle": "2023-08-22T06:59:57.761149Z", + "shell.execute_reply": "2023-08-22T06:59:57.760820Z" } }, "outputs": [], @@ -485,10 +485,10 @@ "id": "d4a8cf16", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:15.802048Z", - "iopub.status.busy": "2023-08-21T02:29:15.801932Z", - "iopub.status.idle": "2023-08-21T02:29:16.552146Z", - "shell.execute_reply": "2023-08-21T02:29:16.550354Z" + "iopub.execute_input": "2023-08-22T06:59:57.762826Z", + "iopub.status.busy": "2023-08-22T06:59:57.762724Z", + "iopub.status.idle": "2023-08-22T06:59:58.384792Z", + "shell.execute_reply": "2023-08-22T06:59:58.384441Z" }, "lines_to_next_cell": 2 }, @@ -530,10 +530,10 @@ "id": "ce40a9ba", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:16.556568Z", - "iopub.status.busy": "2023-08-21T02:29:16.555939Z", - "iopub.status.idle": "2023-08-21T02:29:16.866266Z", - "shell.execute_reply": "2023-08-21T02:29:16.865469Z" + "iopub.execute_input": "2023-08-22T06:59:58.386657Z", + "iopub.status.busy": "2023-08-22T06:59:58.386521Z", + "iopub.status.idle": "2023-08-22T06:59:58.504180Z", + "shell.execute_reply": "2023-08-22T06:59:58.503223Z" }, "lines_to_next_cell": 0 }, @@ -599,10 +599,10 @@ "id": "c7416ff6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:16.869059Z", - "iopub.status.busy": "2023-08-21T02:29:16.868880Z", - "iopub.status.idle": "2023-08-21T02:29:20.216833Z", - "shell.execute_reply": "2023-08-21T02:29:20.216545Z" + "iopub.execute_input": "2023-08-22T06:59:58.509147Z", + "iopub.status.busy": "2023-08-22T06:59:58.508897Z", + "iopub.status.idle": "2023-08-22T07:00:01.677521Z", + "shell.execute_reply": "2023-08-22T07:00:01.677198Z" }, "lines_to_next_cell": 0 }, @@ -653,10 +653,10 @@ "id": "a2ae089b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:20.218513Z", - "iopub.status.busy": "2023-08-21T02:29:20.218396Z", - "iopub.status.idle": "2023-08-21T02:29:20.221477Z", - "shell.execute_reply": "2023-08-21T02:29:20.221172Z" + "iopub.execute_input": "2023-08-22T07:00:01.679228Z", + "iopub.status.busy": "2023-08-22T07:00:01.679111Z", + "iopub.status.idle": "2023-08-22T07:00:01.681995Z", + "shell.execute_reply": "2023-08-22T07:00:01.681709Z" } }, "outputs": [ @@ -695,10 +695,10 @@ "id": "1681a9db", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:20.223098Z", - "iopub.status.busy": "2023-08-21T02:29:20.223012Z", - "iopub.status.idle": "2023-08-21T02:29:20.308656Z", - "shell.execute_reply": "2023-08-21T02:29:20.308356Z" + "iopub.execute_input": "2023-08-22T07:00:01.683590Z", + "iopub.status.busy": "2023-08-22T07:00:01.683477Z", + "iopub.status.idle": "2023-08-22T07:00:01.759136Z", + "shell.execute_reply": "2023-08-22T07:00:01.758804Z" } }, "outputs": [ @@ -741,10 +741,10 @@ "id": "5764b0ba", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:20.310366Z", - "iopub.status.busy": "2023-08-21T02:29:20.310242Z", - "iopub.status.idle": "2023-08-21T02:29:20.927992Z", - "shell.execute_reply": "2023-08-21T02:29:20.927702Z" + "iopub.execute_input": "2023-08-22T07:00:01.760831Z", + "iopub.status.busy": "2023-08-22T07:00:01.760716Z", + "iopub.status.idle": "2023-08-22T07:00:02.384829Z", + "shell.execute_reply": "2023-08-22T07:00:02.384507Z" }, "lines_to_next_cell": 0 }, @@ -775,10 +775,10 @@ "id": "d76f3d3a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:20.929777Z", - "iopub.status.busy": "2023-08-21T02:29:20.929678Z", - "iopub.status.idle": "2023-08-21T02:29:21.021186Z", - "shell.execute_reply": "2023-08-21T02:29:21.020858Z" + "iopub.execute_input": "2023-08-22T07:00:02.387276Z", + "iopub.status.busy": "2023-08-22T07:00:02.386879Z", + "iopub.status.idle": "2023-08-22T07:00:02.468255Z", + "shell.execute_reply": "2023-08-22T07:00:02.467684Z" }, "lines_to_next_cell": 2 }, @@ -828,10 +828,10 @@ "id": "ed25c2d4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:21.022941Z", - "iopub.status.busy": "2023-08-21T02:29:21.022836Z", - "iopub.status.idle": "2023-08-21T02:29:21.043228Z", - "shell.execute_reply": "2023-08-21T02:29:21.042926Z" + "iopub.execute_input": "2023-08-22T07:00:02.470331Z", + "iopub.status.busy": "2023-08-22T07:00:02.470178Z", + "iopub.status.idle": "2023-08-22T07:00:02.491378Z", + "shell.execute_reply": "2023-08-22T07:00:02.491048Z" }, "lines_to_next_cell": 0 }, @@ -857,10 +857,10 @@ "id": "31e99e02", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:21.044846Z", - "iopub.status.busy": "2023-08-21T02:29:21.044745Z", - "iopub.status.idle": "2023-08-21T02:29:23.376539Z", - "shell.execute_reply": "2023-08-21T02:29:23.376256Z" + "iopub.execute_input": "2023-08-22T07:00:02.493549Z", + "iopub.status.busy": "2023-08-22T07:00:02.493371Z", + "iopub.status.idle": "2023-08-22T07:00:07.838494Z", + "shell.execute_reply": "2023-08-22T07:00:07.838064Z" } }, "outputs": [ @@ -912,10 +912,10 @@ "id": "214d0f23", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.378603Z", - "iopub.status.busy": "2023-08-21T02:29:23.378467Z", - "iopub.status.idle": "2023-08-21T02:29:23.380970Z", - "shell.execute_reply": "2023-08-21T02:29:23.380691Z" + "iopub.execute_input": "2023-08-22T07:00:07.840443Z", + "iopub.status.busy": "2023-08-22T07:00:07.840298Z", + "iopub.status.idle": "2023-08-22T07:00:07.842812Z", + "shell.execute_reply": "2023-08-22T07:00:07.842557Z" }, "lines_to_next_cell": 0 }, @@ -977,10 +977,10 @@ "id": "ca7469fb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.382549Z", - "iopub.status.busy": "2023-08-21T02:29:23.382432Z", - "iopub.status.idle": "2023-08-21T02:29:23.450752Z", - "shell.execute_reply": "2023-08-21T02:29:23.450471Z" + "iopub.execute_input": "2023-08-22T07:00:07.844529Z", + "iopub.status.busy": "2023-08-22T07:00:07.844419Z", + "iopub.status.idle": "2023-08-22T07:00:07.900374Z", + "shell.execute_reply": "2023-08-22T07:00:07.899998Z" }, "lines_to_next_cell": 0 }, @@ -989,405 +989,405 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64428165.36474803, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64428165.36474803, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64428069.135193564, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64428069.135193564, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427947.709570706, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427947.709570706, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427794.49147929, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427794.49147929, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427601.15801401, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427601.15801401, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427357.208145335, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427357.208145335, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427049.39312406, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64427049.39312406, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64426660.99818401, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64426660.99818401, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64426170.936871, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64426170.936871, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64425552.60935727, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64425552.60935727, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64424772.46361481, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64424772.46361481, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64423788.18271286, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64423788.18271286, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64422546.402046196, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64422546.402046196, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64420979.836119056, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64420979.836119056, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64419003.66458898, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64419003.66458898, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64416510.99045885, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64416510.99045885, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64413367.138336174, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64413367.138336174, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64409402.50628651, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64409402.50628651, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64404403.61988451, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64404403.61988451, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64398101.96098537, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64398101.96098537, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64390160.05690916, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64390160.05690916, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64380154.22050254, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64380154.22050254, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64367553.23368757, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64367553.23368757, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64351692.17811265, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64351692.17811265, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64331740.55708714, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64331740.55708714, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64306663.85815487, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64306663.85815487, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64275177.83204634, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64275177.83204634, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64235695.09903011, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64235695.09903011, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64186264.367964305, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64186264.367964305, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64124503.75014188, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64124503.75014188, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64047531.61120446, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 64047531.61120446, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63951901.41718618, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63951901.41718618, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63833551.374737374, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63833551.374737374, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63687785.48493876, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63687785.48493876, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63509309.685659595, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63509309.685659595, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63292354.02159835, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63292354.02159835, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63030916.89990266, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 63030916.89990266, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 62719166.29703928, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 62719166.29703928, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 62352019.354438685, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 62352019.354438685, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 61925889.875772476, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 61925889.875772476, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 61439539.89859062, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 61439539.89859062, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 60894903.039219804, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 60894903.039219804, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 60297684.607476555, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 60297684.607476555, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 59657521.16598571, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 59657521.16598571, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 58987535.05051082, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 58987535.05051082, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 58303257.30893663, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 58303257.30893663, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 57621079.35589412, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 57621079.35589412, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 56956552.362989165, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 56956552.362989165, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 56322906.14367991, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 56322906.14367991, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 55730077.752803415, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 55730077.752803415, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 55184365.56435659, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 55184365.56435659, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 54688640.34364891, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 54688640.34364891, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 54242923.97107168, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 54242923.97107168, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 53845116.92275897, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 53845116.92275897, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 53491699.68250863, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 53491699.68250863, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 53178310.76477921, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 53178310.76477921, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52900177.09233121, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52900177.09233121, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52652419.277090184, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52652419.277090184, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52430270.98847021, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52430270.98847021, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52229246.49376922, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52229246.49376922, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52045276.251295805, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 52045276.251295805, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51874817.10761593, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51874817.10761593, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51714935.480955906, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51714935.480955906, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51563358.53546297, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51563358.53546297, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51418487.867063135, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51418487.867063135, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51279371.6204245, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51279371.6204245, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51145634.32609803, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51145634.32609803, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51017369.002990715, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 51017369.002990715, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50895002.06601913, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50895002.06601913, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50779146.50047491, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50779146.50047491, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50670461.07683641, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50670461.07683641, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50569532.273268215, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50569532.273268215, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50476790.981010474, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50476790.981010474, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50392468.80539254, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50392468.80539254, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50316590.69087247, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50316590.69087247, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50248994.15213543, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50248994.15213543, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50189362.60450393, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50189362.60450393, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50137261.69126286, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50137261.69126286, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50092171.83247456, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50092171.83247456, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50053515.0816231, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50053515.0816231, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50020677.61213055, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 50020677.61213055, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49993029.950182974, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49993029.950182974, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49969946.08142715, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49969946.08142715, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49950821.12032734, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49950821.12032734, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49935086.375795275, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49935086.375795275, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49922220.65542218, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49922220.65542218, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49911757.23721766, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49911757.23721766, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49903286.65921827, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49903286.65921827, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49896456.01861009, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49896456.01861009, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49890965.72520982, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49890965.72520982, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49886564.66025478, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49886564.66025478, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49883044.54819732, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49883044.54819732, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49880234.147845834, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49880234.147845834, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49877993.670362815, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49877993.670362815, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49876209.66553557, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49876209.66553557, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49874790.493499264, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49874790.493499264, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49873662.41408341, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49873662.41408341, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49872766.272819825, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49872766.272819825, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49872054.73300109, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49872054.73300109, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49871489.989638604, tolerance: 12885.7065737425\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 49871489.989638604, tolerance: 12885.7065737425\n", " model = cd_fast.enet_coordinate_descent_gram(\n" ] }, @@ -1444,10 +1444,10 @@ "id": "a5b4b3a7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.452873Z", - "iopub.status.busy": "2023-08-21T02:29:23.452757Z", - "iopub.status.idle": "2023-08-21T02:29:23.462335Z", - "shell.execute_reply": "2023-08-21T02:29:23.462029Z" + "iopub.execute_input": "2023-08-22T07:00:07.902654Z", + "iopub.status.busy": "2023-08-22T07:00:07.902513Z", + "iopub.status.idle": "2023-08-22T07:00:07.912659Z", + "shell.execute_reply": "2023-08-22T07:00:07.912286Z" } }, "outputs": [ @@ -1866,10 +1866,10 @@ "id": "ffdcd0c6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.463956Z", - "iopub.status.busy": "2023-08-21T02:29:23.463846Z", - "iopub.status.idle": "2023-08-21T02:29:23.670285Z", - "shell.execute_reply": "2023-08-21T02:29:23.669949Z" + "iopub.execute_input": "2023-08-22T07:00:07.914460Z", + "iopub.status.busy": "2023-08-22T07:00:07.914335Z", + "iopub.status.idle": "2023-08-22T07:00:08.105311Z", + "shell.execute_reply": "2023-08-22T07:00:08.104857Z" }, "lines_to_next_cell": 0 }, @@ -1911,10 +1911,10 @@ "id": "e60d63d3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.671975Z", - "iopub.status.busy": "2023-08-21T02:29:23.671852Z", - "iopub.status.idle": "2023-08-21T02:29:23.674849Z", - "shell.execute_reply": "2023-08-21T02:29:23.674590Z" + "iopub.execute_input": "2023-08-22T07:00:08.107307Z", + "iopub.status.busy": "2023-08-22T07:00:08.107179Z", + "iopub.status.idle": "2023-08-22T07:00:08.110477Z", + "shell.execute_reply": "2023-08-22T07:00:08.110049Z" } }, "outputs": [ @@ -1968,10 +1968,10 @@ "id": "a2253f89", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.676319Z", - "iopub.status.busy": "2023-08-21T02:29:23.676213Z", - "iopub.status.idle": "2023-08-21T02:29:23.678423Z", - "shell.execute_reply": "2023-08-21T02:29:23.678191Z" + "iopub.execute_input": "2023-08-22T07:00:08.112116Z", + "iopub.status.busy": "2023-08-22T07:00:08.112018Z", + "iopub.status.idle": "2023-08-22T07:00:08.114728Z", + "shell.execute_reply": "2023-08-22T07:00:08.114379Z" } }, "outputs": [ @@ -2006,10 +2006,10 @@ "id": "aa10fcf4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.679982Z", - "iopub.status.busy": "2023-08-21T02:29:23.679875Z", - "iopub.status.idle": "2023-08-21T02:29:23.682329Z", - "shell.execute_reply": "2023-08-21T02:29:23.682074Z" + "iopub.execute_input": "2023-08-22T07:00:08.116886Z", + "iopub.status.busy": "2023-08-22T07:00:08.116732Z", + "iopub.status.idle": "2023-08-22T07:00:08.119361Z", + "shell.execute_reply": "2023-08-22T07:00:08.119014Z" }, "lines_to_next_cell": 0 }, @@ -2047,10 +2047,10 @@ "id": "f5bc4121", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.683856Z", - "iopub.status.busy": "2023-08-21T02:29:23.683756Z", - "iopub.status.idle": "2023-08-21T02:29:23.696250Z", - "shell.execute_reply": "2023-08-21T02:29:23.695956Z" + "iopub.execute_input": "2023-08-22T07:00:08.121086Z", + "iopub.status.busy": "2023-08-22T07:00:08.120969Z", + "iopub.status.idle": "2023-08-22T07:00:08.133376Z", + "shell.execute_reply": "2023-08-22T07:00:08.133011Z" } }, "outputs": [ @@ -2058,7 +2058,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.446e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.446e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -2100,10 +2100,10 @@ "id": "e4018437", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.697819Z", - "iopub.status.busy": "2023-08-21T02:29:23.697718Z", - "iopub.status.idle": "2023-08-21T02:29:23.700233Z", - "shell.execute_reply": "2023-08-21T02:29:23.699974Z" + "iopub.execute_input": "2023-08-22T07:00:08.135390Z", + "iopub.status.busy": "2023-08-22T07:00:08.135249Z", + "iopub.status.idle": "2023-08-22T07:00:08.138028Z", + "shell.execute_reply": "2023-08-22T07:00:08.137669Z" }, "lines_to_next_cell": 0 }, @@ -2147,10 +2147,10 @@ "id": "aaa73183", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.701707Z", - "iopub.status.busy": "2023-08-21T02:29:23.701624Z", - "iopub.status.idle": "2023-08-21T02:29:23.709254Z", - "shell.execute_reply": "2023-08-21T02:29:23.708916Z" + "iopub.execute_input": "2023-08-22T07:00:08.140104Z", + "iopub.status.busy": "2023-08-22T07:00:08.139927Z", + "iopub.status.idle": "2023-08-22T07:00:08.147255Z", + "shell.execute_reply": "2023-08-22T07:00:08.146900Z" } }, "outputs": [ @@ -2158,7 +2158,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.486e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.486e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -2205,10 +2205,10 @@ "id": "8f95689e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.711112Z", - "iopub.status.busy": "2023-08-21T02:29:23.710959Z", - "iopub.status.idle": "2023-08-21T02:29:23.718893Z", - "shell.execute_reply": "2023-08-21T02:29:23.718567Z" + "iopub.execute_input": "2023-08-22T07:00:08.149814Z", + "iopub.status.busy": "2023-08-22T07:00:08.149544Z", + "iopub.status.idle": "2023-08-22T07:00:08.157631Z", + "shell.execute_reply": "2023-08-22T07:00:08.157328Z" }, "lines_to_next_cell": 0 }, @@ -2217,7 +2217,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -2262,10 +2262,10 @@ "id": "725a3200", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:23.720467Z", - "iopub.status.busy": "2023-08-21T02:29:23.720361Z", - "iopub.status.idle": "2023-08-21T02:29:24.185363Z", - "shell.execute_reply": "2023-08-21T02:29:24.185015Z" + "iopub.execute_input": "2023-08-22T07:00:08.159712Z", + "iopub.status.busy": "2023-08-22T07:00:08.159508Z", + "iopub.status.idle": "2023-08-22T07:00:08.559312Z", + "shell.execute_reply": "2023-08-22T07:00:08.558977Z" } }, "outputs": [ @@ -2273,207 +2273,207 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.136e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.134e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.134e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.134e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.134e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.133e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.133e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.132e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.132e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.131e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.131e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.130e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.130e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.128e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.128e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.127e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.127e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.124e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.124e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.121e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.121e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.117e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.117e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.113e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.113e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.107e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.107e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.100e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.100e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.091e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.091e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.081e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.081e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.069e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.069e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.055e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.055e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.977e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.977e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.744e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.744e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.494e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.494e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.234e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.234e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.968e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.968e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.704e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.704e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.448e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.448e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.204e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.204e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.977e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.977e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.769e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.769e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.581e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.581e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.412e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.412e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.261e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.261e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.127e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.127e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.008e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 7.008e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.900e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.900e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.803e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.803e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.714e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.714e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.632e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.632e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.554e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.554e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.480e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.480e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.409e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.409e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.342e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.342e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.276e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.276e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.214e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.214e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.154e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.154e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.097e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.097e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.043e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 6.043e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.991e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.991e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.943e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.943e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.898e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.898e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.856e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.856e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.817e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.817e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.780e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.780e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.746e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.746e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.715e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.715e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.687e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.687e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.661e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.661e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.637e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.637e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.616e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.616e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.596e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.596e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.579e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.579e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.563e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.563e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.550e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.550e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.538e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.538e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.528e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.528e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.519e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.519e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.512e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.512e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.506e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.506e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.500e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.500e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.496e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.496e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.493e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.493e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.490e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.490e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.488e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.488e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.486e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.486e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.485e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.485e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.483e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.483e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.483e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.483e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.482e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 5.482e+06, tolerance: 2.272e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.248e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.248e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -2519,10 +2519,10 @@ "id": "823982cc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:24.187182Z", - "iopub.status.busy": "2023-08-21T02:29:24.187049Z", - "iopub.status.idle": "2023-08-21T02:29:27.299737Z", - "shell.execute_reply": "2023-08-21T02:29:27.299435Z" + "iopub.execute_input": "2023-08-22T07:00:08.561312Z", + "iopub.status.busy": "2023-08-22T07:00:08.561182Z", + "iopub.status.idle": "2023-08-22T07:00:11.194918Z", + "shell.execute_reply": "2023-08-22T07:00:11.194585Z" }, "lines_to_next_cell": 0 }, @@ -2531,1007 +2531,1007 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.877e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.877e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.230e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.230e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.097e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.097e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.229e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.229e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.214e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.214e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.096e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.096e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.228e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.228e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.875e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.875e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.095e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.095e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.227e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.227e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.211e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.211e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.873e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.873e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.093e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.093e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.225e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.225e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.209e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.209e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.872e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.872e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.212e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.212e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.870e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.870e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.089e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.089e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.210e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.210e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.204e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.204e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.200e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.200e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.864e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.864e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.082e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.082e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.203e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.203e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.196e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.196e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.860e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.860e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.208e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.208e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.197e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.197e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.855e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.855e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.071e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.071e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.201e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.201e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.191e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.191e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.849e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.849e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.063e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.063e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.194e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.194e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.174e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.174e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.841e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.841e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.184e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.184e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.173e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.173e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.163e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.163e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.172e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.172e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.161e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.161e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.149e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.149e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.820e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.820e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.029e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.029e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.157e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.157e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.146e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.146e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.806e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.806e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.012e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.012e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.139e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.139e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.129e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.129e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.112e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.112e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.789e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.789e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.992e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.992e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.117e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.117e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.107e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.107e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.769e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.769e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.968e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.968e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.081e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.081e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.745e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.745e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.060e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.060e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.051e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.051e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.718e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.718e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.907e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.907e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.015e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.015e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.686e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.686e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.869e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.869e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.975e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.975e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.650e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.650e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.828e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.828e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.938e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.938e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.929e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.929e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.611e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.611e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.783e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.783e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.568e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.568e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.734e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.734e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.834e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.834e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.826e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.826e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.772e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.772e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.524e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.524e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.684e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.684e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.778e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.778e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.770e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.770e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.710e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.710e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.478e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.478e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.633e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.633e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.721e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.721e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.646e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.646e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.432e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.432e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.663e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.663e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.655e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.655e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.388e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.388e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.533e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.533e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.607e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.607e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.599e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.599e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.520e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.520e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.345e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.345e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.486e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.486e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.554e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.554e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.545e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.545e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.460e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.460e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.443e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.443e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.504e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.504e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.494e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.494e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.404e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.404e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.268e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.268e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.403e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.403e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.457e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.457e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.447e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.447e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.352e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.352e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.415e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.415e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.405e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.405e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.333e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.333e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.377e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.377e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.262e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.262e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.177e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.177e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.304e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.304e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.343e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.343e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.331e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.331e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.224e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.224e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.154e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.154e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.278e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.278e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.312e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.312e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.300e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.300e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.133e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.133e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.255e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.255e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.284e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.284e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.272e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.272e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.159e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.159e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.260e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.260e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.247e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.247e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.098e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.098e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.215e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.215e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.237e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.237e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.225e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.225e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.109e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.109e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.083e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.083e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.088e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.088e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.070e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.070e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.182e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.182e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.186e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.186e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.069e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.069e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.058e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.058e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.167e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.167e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.181e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.181e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.169e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.169e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.165e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.165e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.139e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.139e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.149e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.149e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.138e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.138e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.027e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.027e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.126e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.126e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.124e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.124e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.012e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.012e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.017e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.017e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.121e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.121e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.110e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.110e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.102e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.102e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.108e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.108e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.097e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.097e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.982e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.982e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.090e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.090e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.095e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.095e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.804e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.804e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.894e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.894e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.078e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.078e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.071e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.071e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.713e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.713e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.808e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.808e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.067e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.067e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.073e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.073e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.060e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.060e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.627e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.627e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.727e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.727e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.057e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.057e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.062e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.062e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.048e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.048e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.548e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.548e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.650e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.650e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.579e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.579e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.045e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.045e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.406e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.406e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.514e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.514e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.343e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.343e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.454e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.454e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.030e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.030e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.286e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.286e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.402e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.402e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.003e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.003e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.234e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.234e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.355e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.355e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.969e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.969e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.187e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.187e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.314e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.314e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.966e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.966e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.014e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.014e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.914e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.914e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.145e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.145e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.279e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.279e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.010e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.010e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.865e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.865e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.249e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.249e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.843e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.843e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.824e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.824e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.075e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.075e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.223e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.223e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.047e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.047e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.202e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.202e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.743e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.743e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.761e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.761e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.022e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.022e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.184e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.184e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.700e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.700e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.990e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.990e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.737e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.737e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.000e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.000e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.169e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.169e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.663e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.663e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.971e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.971e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.717e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.717e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.982e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.982e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.156e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.156e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.630e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.630e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.956e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.956e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.701e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.701e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.966e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.966e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.146e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.146e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.601e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.601e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.943e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.943e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.688e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.688e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.953e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.953e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.138e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.138e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.575e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.575e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.933e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.933e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.677e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.677e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.942e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.942e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.132e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.132e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.554e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.554e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.924e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.924e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.668e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.668e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.933e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.933e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.126e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.126e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.535e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.535e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.917e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.917e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.661e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.661e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.926e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.926e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.122e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.122e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.520e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.520e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.911e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.911e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.655e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.655e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.920e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.920e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.119e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.119e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.507e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.507e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.906e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.906e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.651e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.651e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.915e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.915e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.116e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.116e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.496e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.496e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.647e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.647e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.911e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.911e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.114e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.114e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.487e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.487e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.899e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.899e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.644e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.644e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.907e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.907e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.112e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.112e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.480e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.480e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.897e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.897e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.642e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.642e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.905e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.905e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.111e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.111e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.895e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.895e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.640e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.640e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.903e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.903e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.110e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.110e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.469e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.469e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.893e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.893e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.639e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.639e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.901e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.901e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.109e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.109e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.465e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.465e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.892e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.892e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.638e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.638e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.900e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.900e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.462e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.462e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.891e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.891e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.637e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.637e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.899e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.899e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.460e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.460e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.898e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.898e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.458e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.458e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.456e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.456e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.889e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.889e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.635e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.635e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.271e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.271e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -3577,10 +3577,10 @@ "id": "b1b7d3b4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:27.301365Z", - "iopub.status.busy": "2023-08-21T02:29:27.301252Z", - "iopub.status.idle": "2023-08-21T02:29:27.401673Z", - "shell.execute_reply": "2023-08-21T02:29:27.401251Z" + "iopub.execute_input": "2023-08-22T07:00:11.196745Z", + "iopub.status.busy": "2023-08-22T07:00:11.196604Z", + "iopub.status.idle": "2023-08-22T07:00:11.287223Z", + "shell.execute_reply": "2023-08-22T07:00:11.286902Z" } }, "outputs": [ @@ -3621,10 +3621,10 @@ "id": "59a69421", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:27.403382Z", - "iopub.status.busy": "2023-08-21T02:29:27.403269Z", - "iopub.status.idle": "2023-08-21T02:29:30.557588Z", - "shell.execute_reply": "2023-08-21T02:29:30.557217Z" + "iopub.execute_input": "2023-08-22T07:00:11.289077Z", + "iopub.status.busy": "2023-08-22T07:00:11.288949Z", + "iopub.status.idle": "2023-08-22T07:00:13.927873Z", + "shell.execute_reply": "2023-08-22T07:00:13.927443Z" } }, "outputs": [ @@ -3632,1007 +3632,1007 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.101e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.233e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.100e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.222e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.879e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.232e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.099e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.221e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.878e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.231e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.877e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.877e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.098e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.230e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.230e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.097e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.097e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.229e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.229e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.219e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.214e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.214e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.876e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.096e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.096e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.228e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.228e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.218e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.875e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.875e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.095e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.095e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.227e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.227e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.216e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.211e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.211e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.873e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.873e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.093e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.093e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.225e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.225e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.215e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.209e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.209e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.872e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.872e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.223e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.212e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.212e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.870e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.870e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.089e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.089e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.220e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.210e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.210e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.204e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.204e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.867e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.086e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.207e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.200e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.200e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.864e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.864e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.082e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.082e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.213e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.203e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.203e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.196e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.196e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.860e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.860e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.077e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.208e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.208e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.197e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.197e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.855e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.855e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.071e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.071e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.201e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.201e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.191e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.191e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.849e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.849e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.063e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.063e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.194e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.194e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.183e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.174e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.174e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.841e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.841e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.054e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.184e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.184e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.173e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.173e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.163e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.163e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.043e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.172e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.172e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.161e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.161e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.149e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.149e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.820e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.820e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.029e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.029e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.157e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.157e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.146e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.146e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.806e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.806e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.012e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.012e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.139e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.139e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.129e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.129e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.112e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.112e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.789e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.789e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.992e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.992e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.117e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.117e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.107e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.107e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.087e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.769e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.769e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.968e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.968e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.091e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.081e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.081e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.058e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.745e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.745e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.060e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.060e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.051e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.051e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.718e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.718e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.907e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.907e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.015e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 2.015e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.686e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.686e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.869e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.869e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.984e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.975e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.975e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.939e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.650e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.650e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.828e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.828e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.938e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.938e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.929e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.929e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.611e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.611e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.783e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.783e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.888e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.880e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.832e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.568e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.568e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.734e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.734e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.834e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.834e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.826e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.826e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.772e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.772e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.524e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.524e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.684e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.684e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.778e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.778e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.770e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.770e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.710e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.710e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.478e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.478e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.633e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.633e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.721e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.721e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.713e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.646e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.646e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.432e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.432e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.663e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.663e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.655e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.655e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.582e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.388e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.388e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.533e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.533e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.607e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.607e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.599e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.599e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.520e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.520e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.345e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.345e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.486e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.486e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.554e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.554e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.545e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.545e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.460e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.460e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.443e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.443e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.504e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.504e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.494e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.494e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.404e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.404e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.268e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.268e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.403e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.403e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.457e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.457e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.447e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.447e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.352e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.352e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.415e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.415e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.405e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.405e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.305e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.333e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.333e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.377e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.377e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.366e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.262e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.262e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.177e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.177e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.304e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.304e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.343e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.343e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.331e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.331e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.224e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.224e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.154e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.154e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.278e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.278e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.312e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.312e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.300e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.300e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.190e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.133e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.133e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.255e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.255e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.284e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.284e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.272e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.272e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.159e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.159e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.234e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.260e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.260e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.247e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.247e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.132e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.098e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.098e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.215e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.215e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.237e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.237e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.225e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.225e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.109e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.109e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.083e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.083e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.217e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.204e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.088e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.088e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.070e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.070e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.182e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.182e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.198e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.186e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.186e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.069e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.069e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.058e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.058e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.167e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.167e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.181e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.181e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.169e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.169e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.165e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.165e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.139e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.139e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.149e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.149e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.138e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.138e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.027e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.027e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.126e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.126e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.135e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.124e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.124e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.012e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.012e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.017e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.017e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.114e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.121e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.121e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.110e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.110e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.102e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.102e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.108e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.108e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.097e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.097e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.982e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.982e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.090e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.090e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.095e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.095e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.804e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.804e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.894e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.894e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.078e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.078e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.084e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.071e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.071e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.713e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.713e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.808e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.808e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.067e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.067e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.073e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.073e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.060e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.060e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.627e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.627e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.727e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.727e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.057e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.057e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.062e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.062e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.048e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.048e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.548e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.548e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.650e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.650e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.047e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.053e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.038e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.579e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.579e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.045e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.045e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.406e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.406e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.514e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.514e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.028e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.037e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.343e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.343e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.454e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.454e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.030e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.030e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.286e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.286e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.402e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.402e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.011e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.024e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.003e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.003e+07, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.234e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.234e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.355e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.355e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.019e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.969e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.969e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.187e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.187e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.314e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.314e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.966e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.966e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.014e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.014e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.914e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.914e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.145e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.145e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.279e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.279e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.010e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.010e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.865e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.865e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.249e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.249e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.843e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.843e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.007e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.824e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.824e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.075e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.075e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.223e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.223e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.004e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.790e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.047e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.047e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.202e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.202e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.743e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.743e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.001e+07, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.761e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.761e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.022e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.022e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.184e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.184e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.700e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.700e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.990e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.990e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.737e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.737e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.000e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.000e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.169e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.169e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.663e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.663e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.971e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.971e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.717e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.717e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.982e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.982e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.156e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.156e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.630e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.630e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.956e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.956e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.701e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.701e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.966e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.966e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.146e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.146e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.601e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.601e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.943e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.943e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.688e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.688e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.953e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.953e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.138e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.138e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.575e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.575e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.933e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.933e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.677e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.677e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.942e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.942e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.132e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.132e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.554e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.554e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.924e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.924e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.668e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.668e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.933e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.933e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.126e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.126e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.535e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.535e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.917e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.917e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.661e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.661e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.926e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.926e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.122e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.122e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.520e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.520e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.911e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.911e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.655e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.655e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.920e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.920e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.119e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.119e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.507e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.507e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.906e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.906e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.651e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.651e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.915e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.915e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.116e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.116e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.496e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.496e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.902e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.647e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.647e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.911e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.911e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.114e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.114e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.487e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.487e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.899e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.899e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.644e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.644e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.907e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.907e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.112e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.112e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.480e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.480e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.897e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.897e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.642e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.642e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.905e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.905e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.111e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.111e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.474e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.895e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.895e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.640e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.640e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.903e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.903e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.110e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.110e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.469e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.469e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.893e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.893e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.639e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.639e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.901e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.901e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.109e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.109e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.465e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.465e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.892e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.892e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.638e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.638e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.900e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.900e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.462e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.462e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.891e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.891e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.637e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.637e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.899e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.899e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.108e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.460e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.460e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.898e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.898e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.458e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.458e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.890e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.636e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.107e+06, tolerance: 3.759e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.456e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.456e+06, tolerance: 4.201e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.889e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.889e+06, tolerance: 4.466e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.635e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 9.635e+06, tolerance: 4.445e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 8.897e+06, tolerance: 4.437e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.271e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.271e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -4711,10 +4711,10 @@ "id": "572b14c3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:30.559540Z", - "iopub.status.busy": "2023-08-21T02:29:30.559406Z", - "iopub.status.idle": "2023-08-21T02:29:30.661941Z", - "shell.execute_reply": "2023-08-21T02:29:30.660478Z" + "iopub.execute_input": "2023-08-22T07:00:13.930022Z", + "iopub.status.busy": "2023-08-22T07:00:13.929865Z", + "iopub.status.idle": "2023-08-22T07:00:14.018201Z", + "shell.execute_reply": "2023-08-22T07:00:14.017805Z" }, "lines_to_next_cell": 2 }, @@ -4760,10 +4760,10 @@ "id": "a6129b36", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:30.663816Z", - "iopub.status.busy": "2023-08-21T02:29:30.663686Z", - "iopub.status.idle": "2023-08-21T02:29:31.013347Z", - "shell.execute_reply": "2023-08-21T02:29:31.012943Z" + "iopub.execute_input": "2023-08-22T07:00:14.020355Z", + "iopub.status.busy": "2023-08-22T07:00:14.020186Z", + "iopub.status.idle": "2023-08-22T07:00:14.305398Z", + "shell.execute_reply": "2023-08-22T07:00:14.305076Z" } }, "outputs": [ @@ -4771,2007 +4771,2007 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795326.355502333, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795326.355502333, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795268.885511458, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795268.885511458, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795196.367825005, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795196.367825005, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795104.862821113, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18795104.862821113, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794989.399687696, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794989.399687696, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794843.706650957, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794843.706650957, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794659.87071198, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794659.87071198, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794427.908521358, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794427.908521358, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794135.22526347, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18794135.22526347, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18793765.932449568, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18793765.932449568, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18793299.98803079, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18793299.98803079, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18792712.112872534, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18792712.112872534, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18791970.425932087, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18791970.425932087, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18791034.72591697, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18791034.72591697, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18789854.32913581, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18789854.32913581, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18788365.350956466, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18788365.350956466, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18786487.290938053, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18786487.290938053, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18784118.748442672, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18784118.748442672, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18781132.05553399, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18781132.05553399, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18777366.566605024, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18777366.566605024, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18772620.289297033, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18772620.289297033, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18766639.479676694, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18766639.479676694, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18759105.758860495, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18759105.758860495, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18749620.243803147, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18749620.243803147, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18737684.132153213, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18737684.132153213, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18722675.157982755, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18722675.157982755, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18703819.37168406, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18703819.37168406, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18680157.84067929, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18680157.84067929, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18650508.189617783, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18650508.189617783, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18613421.503628485, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18613421.503628485, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18567136.14871325, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18567136.14871325, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18509531.699850053, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18509531.699850053, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18438088.608600505, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18438088.608600505, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18349862.649110064, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18349862.649110064, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18241487.557216965, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18241487.557216965, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18109224.25083878, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18109224.25083878, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17949079.523028806, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17949079.523028806, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17757018.994714484, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17757018.994714484, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17529294.98190815, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17529294.98190815, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17262895.457700975, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17262895.457700975, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16956091.882983487, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16956091.882983487, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16609021.736273043, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16609021.736273043, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16224194.650997939, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16224194.650997939, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15806778.142363884, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15806778.142363884, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15364525.127389485, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15364525.127389485, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14907268.75187378, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14907268.75187378, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14446023.624531085, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14446023.624531085, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13991857.160644894, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13991857.160644894, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13554773.727504015, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13554773.727504015, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13142847.182203237, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13142847.182203237, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12761747.456957739, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12761747.456957739, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12414679.232309299, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12414679.232309299, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12102642.724649917, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12102642.724649917, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11824874.692517474, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11824874.692517474, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11579334.50630629, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11579334.50630629, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11363143.416383019, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11363143.416383019, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11172936.696242273, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11172936.696242273, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11005127.92643167, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11005127.92643167, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10856105.032984463, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10856105.032984463, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10722381.625233045, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10722381.625233045, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10600721.735570516, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10600721.735570516, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10488247.552619573, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10488247.552619573, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10382531.68105097, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10382531.68105097, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10281669.161078632, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10281669.161078632, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10184320.545404715, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10184320.545404715, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10089716.55059902, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10089716.55059902, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9997617.850835908, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9997617.850835908, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9908230.155360885, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9908230.155360885, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9822083.085401118, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9822083.085401118, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9739888.930170696, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9739888.930170696, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9662401.666184625, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9662401.666184625, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9590296.226307327, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9590296.226307327, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9524082.854699288, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9524082.854699288, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9464062.902306747, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9464062.902306747, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9410323.196208755, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9410323.196208755, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9362759.024991764, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9362759.024991764, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9321112.753117379, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9321112.753117379, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9285016.290065145, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9285016.290065145, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9254029.627395952, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9254029.627395952, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9227672.214767914, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9227672.214767914, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9205447.27460862, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9205447.27460862, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9186860.578098293, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9186860.578098293, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9171435.130133288, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9171435.130133288, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9158722.527650403, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9158722.527650403, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9148311.191396464, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9148311.191396464, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9139831.50202173, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9139831.50202173, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9132958.012055235, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9132958.012055235, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9127409.145408802, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9127409.145408802, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9122944.972944392, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9122944.972944392, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9119363.705526328, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9119363.705526328, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9116497.490587894, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9116497.490587894, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9114207.980834428, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9114207.980834428, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9112382.008592516, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9112382.008592516, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9110927.575648237, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9110927.575648237, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9109770.269829819, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9109770.269829819, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9108850.148759764, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9108850.148759764, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9108119.08491204, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9108119.08491204, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9107538.538969103, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9107538.538969103, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9107077.714962065, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9107077.714962065, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9106712.046135923, tolerance: 3759.109166869193\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9106712.046135923, tolerance: 3759.109166869193\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005651.632865302, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005651.632865302, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005578.608102243, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005578.608102243, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005486.463074774, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005486.463074774, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005370.192059726, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005370.192059726, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005223.47917251, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005223.47917251, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005038.355660334, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21005038.355660334, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21004804.76767336, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21004804.76767336, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21004510.03120046, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21004510.03120046, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21004138.144828446, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21004138.144828446, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21003668.923421204, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21003668.923421204, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21003076.906345215, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21003076.906345215, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21002329.98203154, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21002329.98203154, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21001387.655909717, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21001387.655909717, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21000198.8704182, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21000198.8704182, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20998699.26312138, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20998699.26312138, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20996807.72107362, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20996807.72107362, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20994422.05552329, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20994422.05552329, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20991413.57989597, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20991413.57989597, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20987620.324921425, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20987620.324921425, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20982838.567338496, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20982838.567338496, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20976812.283196613, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20976812.283196613, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20969220.065253027, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20969220.065253027, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20959658.970863715, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20959658.970863715, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20947624.701018073, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20947624.701018073, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20932487.468798272, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20932487.468798272, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20913462.923603535, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20913462.923603535, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20889577.599545892, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20889577.599545892, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20859628.61984418, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20859628.61984418, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20822137.913488373, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20822137.913488373, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20775302.126054227, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20775302.126054227, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20716940.917180095, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20716940.917180095, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20644448.64953633, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20644448.64953633, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20554757.795455974, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20554757.795455974, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20444326.815649558, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20444326.815649558, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20309170.5956441, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20309170.5956441, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20144956.94257016, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20144956.94257016, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19947196.308887925, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19947196.308887925, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19711550.604615457, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19711550.604615457, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19434276.168588594, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19434276.168588594, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19112791.023677077, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19112791.023677077, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18746315.49762964, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18746315.49762964, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18336483.416578818, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18336483.416578818, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17887774.82963546, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17887774.82963546, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17407607.14883928, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17407607.14883928, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16905965.499829993, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16905965.499829993, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16394560.80209675, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16394560.80209675, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15885645.94315279, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15885645.94315279, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15390736.734407002, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15390736.734407002, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14919517.25785277, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14919517.25785277, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14479140.715843389, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14479140.715843389, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14074002.01810337, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14074002.01810337, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13705921.512677444, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13705921.512677444, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13374594.126102015, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13374594.126102015, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13078142.079861483, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13078142.079861483, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12813645.639316088, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12813645.639316088, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12577583.791150972, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12577583.791150972, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12366168.387483226, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12366168.387483226, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12175587.27845306, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12175587.27845306, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12002182.958268248, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12002182.958268248, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11842589.470659975, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11842589.470659975, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11693840.031875866, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11693840.031875866, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11553447.60800361, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11553447.60800361, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11419454.0438313, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11419454.0438313, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11290441.388440857, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11290441.388440857, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11165501.742342338, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11165501.742342338, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11044168.420816425, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11044168.420816425, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10926319.289729377, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10926319.289729377, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10812069.210340973, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10812069.210340973, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10701669.403435929, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10701669.403435929, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10595426.714498514, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10595426.714498514, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10493648.013477515, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10493648.013477515, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10396608.203056702, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10396608.203056702, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10304536.713966034, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10304536.713966034, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10217616.440012153, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10217616.440012153, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10135989.092876721, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10135989.092876721, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10059761.060749074, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10059761.060749074, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9989004.697692012, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9989004.697692012, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9923752.620593688, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9923752.620593688, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9863986.795334544, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9863986.795334544, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9809627.884194935, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9809627.884194935, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9760531.052715844, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9760531.052715844, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9716491.487344079, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9716491.487344079, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9677258.06531545, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9677258.06531545, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9642549.951165989, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9642549.951165989, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9612070.387835175, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9612070.387835175, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9585514.488134583, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9585514.488134583, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9562571.500908714, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9562571.500908714, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9542924.549681038, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9542924.549681038, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9526251.156759001, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9526251.156759001, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9512226.472533092, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9512226.472533092, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9500529.267319627, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9500529.267319627, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9490849.431706948, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9490849.431706948, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9482895.334901826, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9482895.334901826, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9476399.71781569, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9476399.71781569, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9471123.439398324, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9471123.439398324, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9466857.004635958, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9466857.004635958, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9463420.20844639, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9463420.20844639, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9460660.409301298, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9460660.409301298, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9458449.957484353, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9458449.957484353, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9456683.22035802, tolerance: 4201.186103419478\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9456683.22035802, tolerance: 4201.186103419478\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331946.25629055, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331946.25629055, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331864.018678214, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331864.018678214, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331760.248581372, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331760.248581372, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331629.308755428, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331629.308755428, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331464.086506005, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331464.086506005, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331255.607747704, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22331255.607747704, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22330992.550247405, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22330992.550247405, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22330660.62979839, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22330660.62979839, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22330241.82628314, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22330241.82628314, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22329713.40806704, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22329713.40806704, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22329046.702501133, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22329046.702501133, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22328205.546983715, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22328205.546983715, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22327144.338416774, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22327144.338416774, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22325805.578253012, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22325805.578253012, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22324116.784799173, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22324116.784799173, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22321986.613041975, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22321986.613041975, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22319299.9839329, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22319299.9839329, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22315911.97874348, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22315911.97874348, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22311640.198869713, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22311640.198869713, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22306255.226839963, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22306255.226839963, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22299468.750693016, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22299468.750693016, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22290918.833475478, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22290918.833475478, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22280151.72747749, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22280151.72747749, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22266599.559077755, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22266599.559077755, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22249553.162800502, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22249553.162800502, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22228129.35292585, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22228129.35292585, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22201232.036903117, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22201232.036903117, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22167506.872833706, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22167506.872833706, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22125289.76574775, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22125289.76574775, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22072550.542125095, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22072550.542125095, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22006834.845984127, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22006834.845984127, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21925209.906269174, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21925209.906269174, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21824223.56629905, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21824223.56629905, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21699890.94922881, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21699890.94922881, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21547729.124614064, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21547729.124614064, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21362866.213577304, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21362866.213577304, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21140255.446179498, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21140255.446179498, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20875023.13975618, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20875023.13975618, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20562967.32341789, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20562967.32341789, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20201195.56502676, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20201195.56502676, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19788844.32939185, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19788844.32939185, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19327763.89751004, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19327763.89751004, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18823001.04313301, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18823001.04313301, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18282896.08461045, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18282896.08461045, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17718660.4886989, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17718660.4886989, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17143422.40324079, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17143422.40324079, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16570887.230051238, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16570887.230051238, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16013892.090309372, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16013892.090309372, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15483171.861886727, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15483171.861886727, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14986579.129588084, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14986579.129588084, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14528848.289413737, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14528848.289413737, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14111836.239774454, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14111836.239774454, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13735069.935277399, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13735069.935277399, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13396407.639332836, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13396407.639332836, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13092660.916831579, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13092660.916831579, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12820093.900344713, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12820093.900344713, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12574781.90922219, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12574781.90922219, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12352853.175078167, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12352853.175078167, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12150651.369793259, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12150651.369793259, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11964850.854771722, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11964850.854771722, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11792543.263225015, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11792543.263225015, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11631302.416094316, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11631302.416094316, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11479227.7561279, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11479227.7561279, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11334963.041737791, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11334963.041737791, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11197685.003164051, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11197685.003164051, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11067056.224580359, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11067056.224580359, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10943139.511030385, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10943139.511030385, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10826278.220752902, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10826278.220752902, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10716956.341549171, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10716956.341549171, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10615659.18706467, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10615659.18706467, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10522756.819315987, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10522756.819315987, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10438426.844454892, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10438426.844454892, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10362623.27115231, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10362623.27115231, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10295087.38179537, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10295087.38179537, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10235388.466414705, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10235388.466414705, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10182978.74114095, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10182978.74114095, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10137247.95260475, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10137247.95260475, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10097567.748922419, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10097567.748922419, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10063321.789749103, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10063321.789749103, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10033922.656392608, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10033922.656392608, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10008819.486834103, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10008819.486834103, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9987500.645290056, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9987500.645290056, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9969494.453323793, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9969494.453323793, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9954369.32479691, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9954369.32479691, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9941733.515465437, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9941733.515465437, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9931234.335989065, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9931234.335989065, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9922556.777457738, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9922556.777457738, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9915421.679110043, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9915421.679110043, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9909583.627876062, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9909583.627876062, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9904828.718921196, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9904828.718921196, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9900972.216495434, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9900972.216495434, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9897856.106707212, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9897856.106707212, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9895346.540855931, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9895346.540855931, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9893331.203755055, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9893331.203755055, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9891716.674948297, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9891716.674948297, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9890425.865192825, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9890425.865192825, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9889395.604661888, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9889395.604661888, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9888574.440116646, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9888574.440116646, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9887920.674489552, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9887920.674489552, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9887400.660169175, tolerance: 4466.452064951529\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9887400.660169175, tolerance: 4466.452064951529\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22225193.80408011, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22225193.80408011, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22225110.813517075, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22225110.813517075, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22225006.093373984, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22225006.093373984, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224873.954836704, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224873.954836704, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224707.22016197, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224707.22016197, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224496.83322094, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224496.83322094, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224231.36831536, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22224231.36831536, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22223896.410779048, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22223896.410779048, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22223473.77603032, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22223473.77603032, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22222940.525154293, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22222940.525154293, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22222267.72434169, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22222267.72434169, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22221418.88207672, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22221418.88207672, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22220347.981225494, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22220347.981225494, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22218997.002387535, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22218997.002387535, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22217292.809172478, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22217292.809172478, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22215143.234477364, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22215143.234477364, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22212432.168317866, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22212432.168317866, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22209013.40126823, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22209013.40126823, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22204702.922219783, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22204702.922219783, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22199269.304569546, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22199269.304569546, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22192421.741654057, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22192421.741654057, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22183795.21258787, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22183795.21258787, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22172932.17909693, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22172932.17909693, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22159260.14304964, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22159260.14304964, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22142064.35203175, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22142064.35203175, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22120454.95809202, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22120454.95809202, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22093328.06334204, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22093328.06334204, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22059320.403233726, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22059320.403233726, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22016758.03845356, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22016758.03845356, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21963600.508906867, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21963600.508906867, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21897383.65478575, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21897383.65478575, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21815166.968429696, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21815166.968429696, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21713495.123522323, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21713495.123522323, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21588388.30984886, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21588388.30984886, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21435381.888817236, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21435381.888817236, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21249641.65996918, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21249641.65996918, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21026184.505123127, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21026184.505123127, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20760231.655652393, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20760231.655652393, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20447708.31167379, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20447708.31167379, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20085874.018901825, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20085874.018901825, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19674021.850113407, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19674021.850113407, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19214128.3053442, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19214128.3053442, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18711289.424232315, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18711289.424232315, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18173771.014405873, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18173771.014405873, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17612557.62934444, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17612557.62934444, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17040407.03219554, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17040407.03219554, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16470567.131662391, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16470567.131662391, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15915425.819018744, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15915425.819018744, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15385384.27148134, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15385384.27148134, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14888160.528800251, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14888160.528800251, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14428585.410549453, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14428585.410549453, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14008814.608291918, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14008814.608291918, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13628800.43657365, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13628800.43657365, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13286857.361730725, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13286857.361730725, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12980197.224087035, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12980197.224087035, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12705370.410345197, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12705370.410345197, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12458600.903357476, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12458600.903357476, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12236032.77957509, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12236032.77957509, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12033913.49389702, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12033913.49389702, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11848733.596731743, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11848733.596731743, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11677333.403468838, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11677333.403468838, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11516981.070353946, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11516981.070353946, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11365424.704670552, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11365424.704670552, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11220921.203073826, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11220921.203073826, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11082243.920528807, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11082243.920528807, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10948669.457422748, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10948669.457422748, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10819942.016223667, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10819942.016223667, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10696213.317397818, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10696213.317397818, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10577957.546131799, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10577957.546131799, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10465864.125929628, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10465864.125929628, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10360715.842557454, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10360715.842557454, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10263264.873279892, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10263264.873279892, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10174122.558233691, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10174122.558233691, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10093678.084935276, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10093678.084935276, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10022055.90958463, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10022055.90958463, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9959113.332252601, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9959113.332252601, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9904471.381944738, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9904471.381944738, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9857566.988895562, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9857566.988895562, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9817713.479318874, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9817713.479318874, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9784158.875562938, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9784158.875562938, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9756135.4293958, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9756135.4293958, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9732897.547924208, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9732897.547924208, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9713747.933154197, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9713747.933154197, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9698053.28484727, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9698053.28484727, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9685251.610393653, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9685251.610393653, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9674853.346299471, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9674853.346299471, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9666438.328081315, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9666438.328081315, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9659650.291029936, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9659650.291029936, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9654190.159247063, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9654190.159247063, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9649808.977198932, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9649808.977198932, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9646301.012972398, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9646301.012972398, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9643497.331329834, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9643497.331329834, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9641259.984843817, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9641259.984843817, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9639476.879484767, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9639476.879484767, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9638057.315691978, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9638057.315691978, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9636928.172691077, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9636928.172691077, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9636030.684258943, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9636030.684258943, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9635317.743812287, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9635317.743812287, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9634751.672914779, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9634751.672914779, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9634302.388158696, tolerance: 4445.102149685068\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9634302.388158696, tolerance: 4445.102149685068\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182535.705905367, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182535.705905367, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182443.31748153, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182443.31748153, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182326.738805104, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182326.738805104, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182179.636849403, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22182179.636849403, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181994.021044992, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181994.021044992, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181759.809716668, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181759.809716668, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181464.28327085, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181464.28327085, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181091.39464482, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22181091.39464482, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22180620.89990636, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22180620.89990636, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22180027.262331244, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22180027.262331244, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22179278.27131426, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22179278.27131426, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22178333.30250969, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22178333.30250969, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22177141.126954924, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22177141.126954924, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22175637.153777506, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22175637.153777506, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22173739.962460298, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22173739.962460298, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22171346.945451487, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22171346.945451487, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22168328.83898362, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22168328.83898362, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22164522.86814139, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22164522.86814139, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22159724.170510717, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22159724.170510717, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22153675.090679448, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22153675.090679448, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22146051.856030278, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22146051.856030278, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22136448.05522982, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22136448.05522982, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22124354.250566233, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22124354.250566233, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22109132.97552027, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22109132.97552027, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22089988.320511386, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22089988.320511386, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22065929.327634364, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22065929.327634364, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22035726.555516478, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 22035726.555516478, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21997861.52451259, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21997861.52451259, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21950469.43740475, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21950469.43740475, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21891276.769023754, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21891276.769023754, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21817537.260214396, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21817537.260214396, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21725972.80421009, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21725972.80421009, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21612729.92224466, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21612729.92224466, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21473368.08108258, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21473368.08108258, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21302902.69437747, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21302902.69437747, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21095932.158423126, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 21095932.158423126, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20846882.286273133, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20846882.286273133, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20550398.911674757, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20550398.911674757, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20201904.639180813, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 20201904.639180813, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19798303.254432607, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19798303.254432607, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19338763.60317261, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 19338763.60317261, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18825451.629099563, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18825451.629099563, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18264026.303933263, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 18264026.303933263, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17663705.112665202, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17663705.112665202, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17036766.85903686, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 17036766.85903686, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16397496.223623449, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16397496.223623449, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15760744.92149185, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15760744.92149185, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15140415.226936534, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15140415.226936534, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14548197.66197113, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14548197.66197113, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13992801.316187331, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13992801.316187331, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13479749.374918321, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13479749.374918321, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13011650.716625076, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13011650.716625076, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12588761.536151327, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12588761.536151327, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12209637.009462353, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12209637.009462353, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11871722.016013274, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11871722.016013274, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11571805.12738007, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11571805.12738007, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11306328.206388844, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11306328.206388844, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11071585.798533637, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11071585.798533637, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10863860.419768564, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10863860.419768564, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10679529.96999051, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10679529.96999051, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10515164.967978276, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10515164.967978276, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10367617.395431116, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10367617.395431116, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10234094.932508666, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10234094.932508666, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10112213.557229094, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10112213.557229094, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10000024.23575536, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10000024.23575536, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9896012.57105465, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9896012.57105465, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9799072.614562154, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9799072.614562154, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9708457.890308099, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9708457.890308099, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9623714.619163413, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9623714.619163413, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9544604.25348744, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9544604.25348744, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9471024.212762302, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9471024.212762302, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9402936.228999598, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9402936.228999598, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9340310.144654753, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9340310.144654753, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9283087.29859646, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9283087.29859646, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9231162.854348717, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9231162.854348717, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9184382.359520858, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9184382.359520858, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9142546.024753645, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9142546.024753645, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9105415.114890352, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9105415.114890352, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9072717.557093456, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9072717.557093456, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9044152.703403218, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9044152.703403218, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9019396.685310023, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9019396.685310023, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8998109.575324507, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8998109.575324507, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8979944.333787149, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8979944.333787149, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8964556.387394711, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8964556.387394711, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8951612.3695335, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8951612.3695335, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8940797.002727017, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8940797.002727017, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8931817.822045382, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8931817.822045382, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8924407.976697778, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8924407.976697778, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8918327.548498938, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8918327.548498938, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8913363.779400796, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8913363.779400796, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8909330.473245148, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8909330.473245148, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8906066.743651448, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8906066.743651448, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8903435.248435475, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8903435.248435475, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8901320.0564094, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8901320.0564094, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8899624.301448012, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8899624.301448012, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8898267.772619218, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8898267.772619218, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8897184.565959448, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8897184.565959448, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8896320.890152896, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8896320.890152896, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8895633.08348321, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8895633.08348321, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8895085.869018715, tolerance: 4436.577708196869\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8895085.869018715, tolerance: 4436.577708196869\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.271e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.271e+07, tolerance: 5.332e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -6863,10 +6863,10 @@ "id": "3683157f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.015165Z", - "iopub.status.busy": "2023-08-21T02:29:31.015003Z", - "iopub.status.idle": "2023-08-21T02:29:31.140464Z", - "shell.execute_reply": "2023-08-21T02:29:31.139654Z" + "iopub.execute_input": "2023-08-22T07:00:14.307687Z", + "iopub.status.busy": "2023-08-22T07:00:14.307502Z", + "iopub.status.idle": "2023-08-22T07:00:14.399739Z", + "shell.execute_reply": "2023-08-22T07:00:14.399295Z" } }, "outputs": [ @@ -6910,10 +6910,10 @@ "id": "1d504d1b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.144567Z", - "iopub.status.busy": "2023-08-21T02:29:31.144409Z", - "iopub.status.idle": "2023-08-21T02:29:31.154211Z", - "shell.execute_reply": "2023-08-21T02:29:31.151804Z" + "iopub.execute_input": "2023-08-22T07:00:14.401869Z", + "iopub.status.busy": "2023-08-22T07:00:14.401710Z", + "iopub.status.idle": "2023-08-22T07:00:14.404500Z", + "shell.execute_reply": "2023-08-22T07:00:14.404205Z" } }, "outputs": [ @@ -6949,10 +6949,10 @@ "id": "8503f6ed", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.164012Z", - "iopub.status.busy": "2023-08-21T02:29:31.163779Z", - "iopub.status.idle": "2023-08-21T02:29:31.173705Z", - "shell.execute_reply": "2023-08-21T02:29:31.169330Z" + "iopub.execute_input": "2023-08-22T07:00:14.406204Z", + "iopub.status.busy": "2023-08-22T07:00:14.406092Z", + "iopub.status.idle": "2023-08-22T07:00:14.408483Z", + "shell.execute_reply": "2023-08-22T07:00:14.408172Z" }, "lines_to_next_cell": 0 }, @@ -7014,10 +7014,10 @@ "id": "47ab71ff", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.190830Z", - "iopub.status.busy": "2023-08-21T02:29:31.190341Z", - "iopub.status.idle": "2023-08-21T02:29:31.196927Z", - "shell.execute_reply": "2023-08-21T02:29:31.195551Z" + "iopub.execute_input": "2023-08-22T07:00:14.410278Z", + "iopub.status.busy": "2023-08-22T07:00:14.410146Z", + "iopub.status.idle": "2023-08-22T07:00:14.412596Z", + "shell.execute_reply": "2023-08-22T07:00:14.412250Z" } }, "outputs": [], @@ -7041,10 +7041,10 @@ "id": "825b7073", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.199687Z", - "iopub.status.busy": "2023-08-21T02:29:31.199561Z", - "iopub.status.idle": "2023-08-21T02:29:31.520903Z", - "shell.execute_reply": "2023-08-21T02:29:31.520496Z" + "iopub.execute_input": "2023-08-22T07:00:14.414295Z", + "iopub.status.busy": "2023-08-22T07:00:14.414146Z", + "iopub.status.idle": "2023-08-22T07:00:14.676526Z", + "shell.execute_reply": "2023-08-22T07:00:14.676174Z" }, "lines_to_next_cell": 0 }, @@ -7053,2007 +7053,2007 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002961.893047336, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002961.893047336, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002909.292721532, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002909.292721532, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002842.919898538, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002842.919898538, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002759.16890147, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002759.16890147, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002653.490324104, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002653.490324104, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002520.144170538, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002520.144170538, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002351.888507718, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002351.888507718, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002139.586836109, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16002139.586836109, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16001871.713040235, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16001871.713040235, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16001533.727331886, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16001533.727331886, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16001107.28977405, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16001107.28977405, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16000569.269442707, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16000569.269442707, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999890.496647634, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999890.496647634, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999034.192416634, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999034.192416634, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15997953.993094172, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15997953.993094172, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15996591.467783943, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15996591.467783943, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15994873.001788342, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15994873.001788342, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15992705.889472542, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15992705.889472542, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15989973.444502639, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15989973.444502639, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15986528.893835295, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15986528.893835295, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15982187.774395373, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15982187.774395373, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15976718.499356627, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15976718.499356627, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15969830.707495732, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15969830.707495732, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15961160.960501963, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15961160.960501963, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15950255.320705947, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15950255.320705947, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15936548.344581451, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15936548.344581451, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15919338.096469924, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15919338.096469924, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15897756.97009871, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15897756.97009871, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15870738.473491088, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15870738.473491088, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15836980.785622943, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15836980.785622943, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15794908.961932577, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15794908.961932577, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15742639.305781398, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15742639.305781398, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15677951.783964379, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15677951.783964379, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15598279.520216344, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15598279.520216344, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15500728.213326858, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15500728.213326858, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15382142.225333132, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15382142.225333132, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15239236.776243072, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15239236.776243072, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15068814.890988702, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15068814.890988702, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14868080.263148528, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14868080.263148528, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14635039.685599191, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14635039.685599191, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14368959.698660212, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14368959.698660212, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14070805.23862632, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14070805.23862632, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13743554.88143778, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13743554.88143778, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13392276.560592549, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13392276.560592549, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13023877.88091306, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13023877.88091306, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12646520.933576018, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12646520.933576018, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12268792.343592053, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12268792.343592053, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11898803.095559342, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11898803.095559342, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11543417.93091813, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11543417.93091813, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11207766.718773343, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11207766.718773343, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10895093.611569963, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10895093.611569963, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10606899.312997252, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10606899.312997252, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10343266.88124088, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10343266.88124088, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10103247.353431445, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10103247.353431445, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9885208.910573516, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9885208.910573516, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9687100.478192497, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9687100.478192497, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9506625.781409387, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9506625.781409387, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9341352.903950285, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9341352.903950285, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9188793.402093235, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9188793.402093235, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9046478.453631114, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9046478.453631114, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8912045.904589174, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8912045.904589174, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8783339.107432563, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8783339.107432563, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8658509.901020331, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8658509.901020331, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8536113.828113679, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8536113.828113679, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8415183.975072118, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8415183.975072118, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8295269.742745581, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8295269.742745581, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8176429.120013418, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8176429.120013418, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8059168.8293056125, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8059168.8293056125, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7944335.999206969, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7944335.999206969, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7832975.645216511, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7832975.645216511, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7726176.614947152, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7726176.614947152, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7624931.461247044, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7624931.461247044, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7530031.627469164, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7530031.627469164, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7442009.746564693, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7442009.746564693, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7361129.1469736025, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7361129.1469736025, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7287410.63533624, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7287410.63533624, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7220681.095616933, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7220681.095616933, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7160628.395404535, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7160628.395404535, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7106851.48376607, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7106851.48376607, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7058900.76970095, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7058900.76970095, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7016308.880858365, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7016308.880858365, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6978613.911777701, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6978613.911777701, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6945376.571027264, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6945376.571027264, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6916191.049528801, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6916191.049528801, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6890688.79244657, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6890688.79244657, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6868535.393319955, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6868535.393319955, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6849422.765039895, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6849422.765039895, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6833060.05095333, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6833060.05095333, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6819166.544534292, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6819166.544534292, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6807468.458908728, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6807468.458908728, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6797699.628345776, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6797699.628345776, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6789604.944998693, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6789604.944998693, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6782944.868629447, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6782944.868629447, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6777499.565630652, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6777499.565630652, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6773071.791553852, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6773071.791553852, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6769488.209512218, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6769488.209512218, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6766599.256783063, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6766599.256783063, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6764277.892213011, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6764277.892213011, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6762417.6162482, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6762417.6162482, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6760930.116967933, tolerance: 3200.6325551004925\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6760930.116967933, tolerance: 3200.6325551004925\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173612.82487654, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173612.82487654, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173560.33151807, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173560.33151807, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173494.093703294, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173494.093703294, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173410.51311625, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173410.51311625, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173305.049649913, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173305.049649913, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173171.975059805, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173171.975059805, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173004.062268812, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15173004.062268812, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15172792.193566969, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15172792.193566969, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15172524.866617758, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15172524.866617758, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15172187.571748763, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15172187.571748763, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15171762.00720005, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15171762.00720005, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15171225.090500388, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15171225.090500388, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15170547.71354342, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15170547.71354342, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15169693.175771877, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15169693.175771877, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15168615.213598879, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15168615.213598879, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15167255.524179863, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15167255.524179863, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15165540.657224856, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15165540.657224856, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15163378.11903821, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15163378.11903821, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15160651.497821936, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15160651.497821936, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15157214.378191706, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15157214.378191706, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15152882.766135195, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15152882.766135195, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15147425.6946986, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15147425.6946986, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15140553.628850497, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15140553.628850497, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15131904.241777299, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15131904.241777299, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15121025.105980713, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15121025.105980713, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15107352.850599289, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15107352.850599289, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15090188.41286841, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15090188.41286841, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15068668.205066573, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15068668.205066573, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15041731.400110113, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15041731.400110113, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15008084.208955988, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15008084.208955988, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14966163.110870235, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14966163.110870235, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14914100.653844737, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14914100.653844737, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14849699.805850953, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14849699.805850953, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14770425.961151276, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14770425.961151276, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14673429.41690654, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14673429.41690654, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14555614.815015966, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14555614.815015966, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14413776.349016687, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14413776.349016687, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14244816.178940995, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14244816.178940995, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14046055.366934752, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14046055.366934752, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13815628.708094303, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13815628.708094303, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13552926.205683708, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13552926.205683708, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13259008.940702371, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13259008.940702371, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12936897.573228309, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12936897.573228309, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12591625.616217315, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12591625.616217315, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12229982.920676824, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12229982.920676824, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11859948.802383406, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11859948.802383406, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11489906.8603167, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11489906.8603167, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11127805.377401602, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11127805.377401602, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10780443.14443526, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10780443.14443526, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10453012.587348029, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10453012.587348029, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10148944.578529166, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10148944.578529166, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9870012.667698365, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9870012.667698365, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9616601.230672905, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9616601.230672905, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9388032.941233683, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9388032.941233683, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9182876.289070565, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9182876.289070565, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8999193.791535858, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8999193.791535858, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8834727.19434187, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8834727.19434187, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8687036.347689679, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8687036.347689679, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8553612.383287674, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8553612.383287674, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8431979.280234471, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8431979.280234471, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8319788.946660187, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8319788.946660187, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8214909.054690647, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8214909.054690647, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8115501.1056430675, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8115501.1056430675, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8020086.35524954, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8020086.35524954, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7927596.53846852, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7927596.53846852, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7837403.822275469, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7837403.822275469, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7749321.535335509, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7749321.535335509, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7663566.802084766, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7663566.802084766, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7580680.550684168, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7580680.550684168, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7501409.564666606, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7501409.564666606, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7426566.500521793, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7426566.500521793, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7356892.242162683, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7356892.242162683, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7292946.117484922, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7292946.117484922, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7235042.041596897, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7235042.041596897, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7183235.551674365, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7183235.551674365, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7137353.553695727, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7137353.553695727, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7097050.348456673, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7097050.348456673, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7061872.012726546, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7061872.012726546, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7031315.123405474, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7031315.123405474, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7004872.089238734, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7004872.089238734, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6982061.123036072, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6982061.123036072, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6962442.578610088, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6962442.578610088, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6945624.890073966, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6945624.890073966, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6931263.4663270125, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6931263.4663270125, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6919055.476661856, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6919055.476661856, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6908732.977539104, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6908732.977539104, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6900056.2920428645, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6900056.2920428645, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6892808.858171555, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6892808.858171555, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6886793.977603645, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6886793.977603645, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6881833.233569127, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6881833.233569127, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6877765.97498893, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6877765.97498893, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6874449.207170451, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6874449.207170451, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6871757.386867455, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6871757.386867455, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6869581.853912757, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6869581.853912757, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6867829.838852352, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6867829.838852352, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6866423.119345377, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6866423.119345377, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6865296.456501478, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6865296.456501478, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6864395.94700243, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6864395.94700243, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6863677.402652601, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6863677.402652601, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6863104.834999971, tolerance: 3034.7626598069196\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6863104.834999971, tolerance: 3034.7626598069196\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16000126.775776321, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16000126.775776321, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16000067.997791689, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16000067.997791689, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999993.829780785, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999993.829780785, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999900.242584623, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999900.242584623, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999782.152469946, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999782.152469946, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999633.14527111, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999633.14527111, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999445.128467944, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999445.128467944, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999207.892430544, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15999207.892430544, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15998908.557207122, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15998908.557207122, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15998530.875140417, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15998530.875140417, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15998054.351968959, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15998054.351968959, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15997453.139532348, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15997453.139532348, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15996694.641307216, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15996694.641307216, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15995737.757220387, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15995737.757220387, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15994530.675893765, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15994530.675893765, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15993008.099962447, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15993008.099962447, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15991087.762599917, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15991087.762599917, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15988666.060097354, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15988666.060097354, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15985612.585588472, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15985612.585588472, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15981763.302383827, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15981763.302383827, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15976912.042096594, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15976912.042096594, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15970799.954194367, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15970799.954194367, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15963102.47325135, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15963102.47325135, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15953413.314912459, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15953413.314912459, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15941224.973906962, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15941224.973906962, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15925905.198558565, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15925905.198558565, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15906668.990428165, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15906668.990428165, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15882545.878220897, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15882545.878220897, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15852342.621036042, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15852342.621036042, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15814602.219371142, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15814602.219371142, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15767561.301116722, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15767561.301116722, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15709109.781098895, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15709109.781098895, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15636759.341258615, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15636759.341258615, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15547630.840385439, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15547630.840385439, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15438475.105455775, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15438475.105455775, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15305746.07465526, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15305746.07465526, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15145748.542592412, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15145748.542592412, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14954882.27386727, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14954882.27386727, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14729996.36384661, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14729996.36384661, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14468848.510940228, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14468848.510940228, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14170631.317143818, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14170631.317143818, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13836485.361873377, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13836485.361873377, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13469879.089990832, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13469879.089990832, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13076719.754361462, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13076719.754361462, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12665089.79937819, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12665089.79937819, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12244586.676668119, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12244586.676668119, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11825360.36369123, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11825360.36369123, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11417044.801169304, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11417044.801169304, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11027817.645702794, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11027817.645702794, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10663776.910200799, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10663776.910200799, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10328716.2675956, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10328716.2675956, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10024263.64783793, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10024263.64783793, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9750266.819731826, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9750266.819731826, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9505284.688773429, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9505284.688773429, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9287065.61072085, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9287065.61072085, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9092940.776433397, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9092940.776433397, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8920108.266351493, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8920108.266351493, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8765816.866835387, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8765816.866835387, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8627473.905487, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8627473.905487, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8502702.196109628, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8502702.196109628, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8389365.458262948, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8389365.458262948, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8285575.962199782, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8285575.962199782, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8189695.129107317, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8189695.129107317, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8100335.848355204, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8100335.848355204, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8016371.614804332, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8016371.614804332, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7936951.343980087, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7936951.343980087, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7861511.843847987, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7861511.843847987, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7789775.81877588, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7789775.81877588, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7721724.491724883, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7721724.491724883, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7657540.53569288, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7657540.53569288, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7597526.506006125, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7597526.506006125, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7542012.431576015, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7542012.431576015, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7491270.131106991, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7491270.131106991, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7445449.741931618, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7445449.741931618, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7404547.164364969, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7404547.164364969, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7368402.734578147, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7368402.734578147, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7336724.612267373, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7336724.612267373, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7309126.908337014, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7309126.908337014, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7285172.53934286, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7285172.53934286, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7264413.0266303, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7264413.0266303, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7246420.465473388, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7246420.465473388, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7230809.549602925, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7230809.549602925, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7217249.407961924, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7217249.407961924, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7205466.206412938, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7205466.206412938, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7195238.325930048, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7195238.325930048, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7186386.647782039, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7186386.647782039, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7178762.875061372, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7178762.875061372, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7172238.602284237, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7172238.602284237, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7166697.001612171, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7166697.001612171, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7162027.848205515, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7162027.848205515, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7158125.584421616, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7158125.584421616, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7154889.512672326, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7154889.512672326, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7152225.062096559, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7152225.062096559, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7150045.262096591, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7150045.262096591, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7148271.882784204, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7148271.882784204, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7146836.014641162, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7146836.014641162, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7145678.080780019, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7145678.080780019, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7144747.393668608, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7144747.393668608, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7144001.407092072, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7144001.407092072, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7143404.805305656, tolerance: 3200.070250165819\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7143404.805305656, tolerance: 3200.070250165819\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766426.844425442, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766426.844425442, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766379.012219734, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766379.012219734, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766318.655993313, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766318.655993313, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766242.496938994, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766242.496938994, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766146.398082258, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766146.398082258, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766025.13980752, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13766025.13980752, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765872.136748439, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765872.136748439, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765679.08077331, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765679.08077331, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765435.490848666, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765435.490848666, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765128.145612368, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13765128.145612368, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13764740.368286435, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13764740.368286435, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13764251.12581003, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13764251.12581003, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13763633.894413952, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13763633.894413952, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13762855.231859002, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13762855.231859002, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13761872.98172164, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13761872.98172164, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13760634.01686267, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13760634.01686267, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13759071.406945651, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13759071.406945651, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13757100.867966294, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13757100.867966294, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13754616.31968939, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13754616.31968939, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13751484.339396805, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13751484.339396805, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13747537.257695232, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13747537.257695232, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13742564.595583746, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13742564.595583746, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13736302.49455343, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13736302.49455343, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13728420.749109622, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13728420.749109622, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13718507.02436845, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13718507.02436845, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13706047.848124275, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13706047.848124275, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13690406.03569032, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13690406.03569032, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13670794.381086988, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13670794.381086988, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13646245.795015218, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13646245.795015218, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13615580.679837886, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13615580.679837886, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13577373.323622873, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13577373.323622873, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13529920.608156208, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13529920.608156208, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13471218.48980598, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13471218.48980598, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13398954.581488008, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13398954.581488008, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13310528.590455977, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13310528.590455977, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13203115.797389356, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13203115.797389356, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13073790.981404455, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13073790.981404455, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12919729.112886174, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12919729.112886174, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12738491.873820404, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12738491.873820404, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12528392.752768412, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12528392.752768412, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12288907.120278118, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12288907.120278118, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12021061.050642934, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12021061.050642934, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11727704.457379244, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11727704.457379244, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11413566.98420337, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11413566.98420337, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11085024.381464427, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11085024.381464427, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10749570.986969216, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10749570.986969216, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10415080.823900381, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10415080.823900381, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10089009.138994666, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10089009.138994666, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9777704.218602655, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9777704.218602655, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9485957.157639354, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9485957.157639354, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9216836.907742979, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9216836.907742979, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8971777.239570614, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8971777.239570614, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8750831.806329573, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8750831.806329573, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8553002.845594905, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8553002.845594905, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8376568.552591967, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8376568.552591967, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8219365.99395707, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8219365.99395707, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8079015.288983279, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8079015.288983279, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7953088.9445123505, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7953088.9445123505, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7839237.297915861, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7839237.297915861, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7735280.8174845725, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7735280.8174845725, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7639277.0523840925, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7639277.0523840925, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7549567.214150196, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7549567.214150196, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7464805.436922483, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7464805.436922483, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7383972.203368484, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7383972.203368484, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7306371.938584399, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7306371.938584399, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7231613.9732326735, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7231613.9732326735, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7159576.877369866, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7159576.877369866, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7090358.567763316, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7090358.567763316, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7024217.2241215855, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7024217.2241215855, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6961509.172985473, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6961509.172985473, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6902628.941757254, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6902628.941757254, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6847954.742128507, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6847954.742128507, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6797801.388530005, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6797801.388530005, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6752382.798167879, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6752382.798167879, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6711786.944628094, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6711786.944628094, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6675965.981966857, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6675965.981966857, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6644742.448857503, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6644742.448857503, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6617829.550839442, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6617829.550839442, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6594860.867273544, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6594860.867273544, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6575423.588385814, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6575423.588385814, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6559089.833983606, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6559089.833983606, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6545442.225937976, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6545442.225937976, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6534091.895329608, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6534091.895329608, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6524688.873515937, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6524688.873515937, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6516926.039701696, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6516926.039701696, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6510538.426567688, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6510538.426567688, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6505299.7780512385, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6505299.7780512385, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6501017.943079299, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6501017.943079299, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6497530.176477653, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6497530.176477653, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6494698.902794392, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6494698.902794392, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6492408.111473216, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6492408.111473216, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6490560.3336993465, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6490560.3336993465, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6489074.074242126, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6489074.074242126, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6487881.578697735, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6487881.578697735, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6486926.855244275, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6486926.855244275, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6486163.908028902, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6486163.908028902, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6485555.163897053, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6485555.163897053, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6485070.084972435, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6485070.084972435, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6484683.961142942, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6484683.961142942, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6484376.8736711275, tolerance: 2753.321903486231\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6484376.8736711275, tolerance: 2753.321903486231\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123836.286658319, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123836.286658319, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123762.414447501, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123762.414447501, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123669.200043006, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123669.200043006, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123551.579596577, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123551.579596577, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123403.163871313, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123403.163871313, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123215.891543608, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16123215.891543608, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16122979.591935372, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16122979.591935372, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16122681.433587788, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16122681.433587788, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16122305.228986472, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16122305.228986472, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16121830.55809336, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16121830.55809336, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16121231.663752725, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16121231.663752725, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16120476.060052717, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16120476.060052717, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16119522.779778486, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16119522.779778486, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16118320.168518286, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16118320.168518286, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16116803.109996723, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16116803.109996723, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16114889.538918179, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16114889.538918179, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16112476.063036688, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16112476.063036688, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16109432.47434148, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16109432.47434148, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16105594.879294181, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16105594.879294181, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16100757.119470121, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16100757.119470121, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16094660.087017829, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16094660.087017829, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16086978.46580684, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16086978.46580684, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16077304.35332688, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16077304.35332688, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16065127.149018394, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16065127.149018394, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16049809.047450969, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16049809.047450969, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16030555.476241706, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16030555.476241706, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16006379.911872495, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 16006379.911872495, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15976062.758394275, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15976062.758394275, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15938104.483596483, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15938104.483596483, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15890674.11469827, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15890674.11469827, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15831555.686060235, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15831555.686060235, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15758097.525340755, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15758097.525340755, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15667172.578206709, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15667172.578206709, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15555162.420748936, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15555162.420748936, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15417983.020182043, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15417983.020182043, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15251175.908593165, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15251175.908593165, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15050092.453317674, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 15050092.453317674, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14810198.177746587, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14810198.177746587, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14527514.082835246, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14527514.082835246, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14199187.811678281, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 14199187.811678281, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13824146.920817537, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13824146.920817537, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13403734.027286602, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 13403734.027286602, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12942174.869677957, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12942174.869677957, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12446711.659031235, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 12446711.659031235, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11927272.408043081, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11927272.408043081, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11395650.820912804, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 11395650.820912804, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10864314.587176824, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10864314.587176824, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10345084.699656613, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 10345084.699656613, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9847974.664610261, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9847974.664610261, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9380422.144947704, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 9380422.144947704, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8947015.008946363, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8947015.008946363, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8549670.25861056, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8549670.25861056, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8188124.101396974, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 8188124.101396974, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7860558.677097185, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7860558.677097185, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7564216.251072414, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7564216.251072414, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7295907.831051512, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7295907.831051512, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7052382.339382325, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 7052382.339382325, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6830565.9531656, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6830565.9531656, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6627701.871803495, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6627701.871803495, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6441421.548990706, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6441421.548990706, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6269768.629955583, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6269768.629955583, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6111186.722532658, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 6111186.722532658, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5964477.8422521455, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5964477.8422521455, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5828739.876908956, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5828739.876908956, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5703294.550898104, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5703294.550898104, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5587617.998651163, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5587617.998651163, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5481282.987854576, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5481282.987854576, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5383916.678079197, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5383916.678079197, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5295172.882818847, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5295172.882818847, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5214714.536832884, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5214714.536832884, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5142200.898831903, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5142200.898831903, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5077274.992035702, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5077274.992035702, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5019549.576235791, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 5019549.576235791, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4968593.444998971, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4968593.444998971, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4923922.319001433, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4923922.319001433, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4884998.717484867, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4884998.717484867, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4851242.93844572, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4851242.93844572, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4822053.96370539, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4822053.96370539, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4796836.339338534, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4796836.339338534, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4775027.808895556, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4775027.808895556, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4756122.72319144, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4756122.72319144, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4739687.533593078, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4739687.533593078, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4725366.495343714, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4725366.495343714, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4712877.711579567, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4712877.711579567, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4702001.540622955, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4702001.540622955, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4692564.7733192, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4692564.7733192, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4684424.413915036, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4684424.413915036, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4677454.213645212, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4677454.213645212, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4671535.662147184, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4671535.662147184, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4666553.581406483, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4666553.581406483, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4662395.34181063, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4662395.34181063, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4658952.2530382, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4658952.2530382, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4656121.7760819215, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4656121.7760819215, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4653809.600037627, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4653809.600037627, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4651931.081491712, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4651931.081491712, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4650411.90595999, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4650411.90595999, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4649188.052146216, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4649188.052146216, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4648205.23751574, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4648205.23751574, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4647418.038791819, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4647418.038791819, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4646788.852992944, tolerance: 3224.823681413525\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:614: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations. Duality gap: 4646788.852992944, tolerance: 3224.823681413525\n", " model = cd_fast.enet_coordinate_descent_gram(\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 3.855e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1/lib/python3.10/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did not converge. You might want to increase the number of iterations, check the scale of the features or consider increasing regularisation. Duality gap: 1.153e+07, tolerance: 3.855e+03 Linear regression models with null weight for the l1 regularization term are more efficiently fitted using one of the solvers implemented in sklearn.linear_model.Ridge/RidgeCV instead.\n", " model = cd_fast.enet_coordinate_descent(\n" ] }, @@ -9107,10 +9107,10 @@ "id": "efb2d25e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.523410Z", - "iopub.status.busy": "2023-08-21T02:29:31.523272Z", - "iopub.status.idle": "2023-08-21T02:29:31.579951Z", - "shell.execute_reply": "2023-08-21T02:29:31.579678Z" + "iopub.execute_input": "2023-08-22T07:00:14.678953Z", + "iopub.status.busy": "2023-08-22T07:00:14.678802Z", + "iopub.status.idle": "2023-08-22T07:00:14.728316Z", + "shell.execute_reply": "2023-08-22T07:00:14.727946Z" }, "lines_to_next_cell": 2 }, @@ -9143,10 +9143,10 @@ "id": "5d2977a4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.581483Z", - "iopub.status.busy": "2023-08-21T02:29:31.581387Z", - "iopub.status.idle": "2023-08-21T02:29:31.592388Z", - "shell.execute_reply": "2023-08-21T02:29:31.592127Z" + "iopub.execute_input": "2023-08-22T07:00:14.730133Z", + "iopub.status.busy": "2023-08-22T07:00:14.730000Z", + "iopub.status.idle": "2023-08-22T07:00:14.740248Z", + "shell.execute_reply": "2023-08-22T07:00:14.739889Z" }, "lines_to_next_cell": 0 }, @@ -9177,10 +9177,10 @@ "id": "0d833201", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.593898Z", - "iopub.status.busy": "2023-08-21T02:29:31.593816Z", - "iopub.status.idle": "2023-08-21T02:29:31.766535Z", - "shell.execute_reply": "2023-08-21T02:29:31.766109Z" + "iopub.execute_input": "2023-08-22T07:00:14.742261Z", + "iopub.status.busy": "2023-08-22T07:00:14.742118Z", + "iopub.status.idle": "2023-08-22T07:00:14.896514Z", + "shell.execute_reply": "2023-08-22T07:00:14.896137Z" }, "lines_to_next_cell": 0 }, @@ -9220,10 +9220,10 @@ "id": "bfbf2fe3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.768327Z", - "iopub.status.busy": "2023-08-21T02:29:31.768191Z", - "iopub.status.idle": "2023-08-21T02:29:31.770716Z", - "shell.execute_reply": "2023-08-21T02:29:31.770428Z" + "iopub.execute_input": "2023-08-22T07:00:14.898477Z", + "iopub.status.busy": "2023-08-22T07:00:14.898358Z", + "iopub.status.idle": "2023-08-22T07:00:14.900774Z", + "shell.execute_reply": "2023-08-22T07:00:14.900366Z" } }, "outputs": [ @@ -9256,10 +9256,10 @@ "id": "ccb9a209", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.772272Z", - "iopub.status.busy": "2023-08-21T02:29:31.772160Z", - "iopub.status.idle": "2023-08-21T02:29:31.881691Z", - "shell.execute_reply": "2023-08-21T02:29:31.881374Z" + "iopub.execute_input": "2023-08-22T07:00:14.902539Z", + "iopub.status.busy": "2023-08-22T07:00:14.902374Z", + "iopub.status.idle": "2023-08-22T07:00:14.997062Z", + "shell.execute_reply": "2023-08-22T07:00:14.996746Z" } }, "outputs": [ @@ -9303,10 +9303,10 @@ "id": "40eff15b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.883735Z", - "iopub.status.busy": "2023-08-21T02:29:31.883609Z", - "iopub.status.idle": "2023-08-21T02:29:31.886519Z", - "shell.execute_reply": "2023-08-21T02:29:31.886178Z" + "iopub.execute_input": "2023-08-22T07:00:14.998878Z", + "iopub.status.busy": "2023-08-22T07:00:14.998760Z", + "iopub.status.idle": "2023-08-22T07:00:15.001284Z", + "shell.execute_reply": "2023-08-22T07:00:15.000943Z" } }, "outputs": [ @@ -9373,10 +9373,10 @@ "id": "2bd0cc9c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.888390Z", - "iopub.status.busy": "2023-08-21T02:29:31.888274Z", - "iopub.status.idle": "2023-08-21T02:29:31.893813Z", - "shell.execute_reply": "2023-08-21T02:29:31.893422Z" + "iopub.execute_input": "2023-08-22T07:00:15.003376Z", + "iopub.status.busy": "2023-08-22T07:00:15.003216Z", + "iopub.status.idle": "2023-08-22T07:00:15.007328Z", + "shell.execute_reply": "2023-08-22T07:00:15.007008Z" } }, "outputs": [ @@ -9417,10 +9417,10 @@ "id": "f188c54a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.895683Z", - "iopub.status.busy": "2023-08-21T02:29:31.895544Z", - "iopub.status.idle": "2023-08-21T02:29:31.900117Z", - "shell.execute_reply": "2023-08-21T02:29:31.899738Z" + "iopub.execute_input": "2023-08-22T07:00:15.008975Z", + "iopub.status.busy": "2023-08-22T07:00:15.008880Z", + "iopub.status.idle": "2023-08-22T07:00:15.012449Z", + "shell.execute_reply": "2023-08-22T07:00:15.012179Z" } }, "outputs": [ @@ -9460,10 +9460,10 @@ "id": "8be53659", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:31.902369Z", - "iopub.status.busy": "2023-08-21T02:29:31.902221Z", - "iopub.status.idle": "2023-08-21T02:29:32.087080Z", - "shell.execute_reply": "2023-08-21T02:29:32.086738Z" + "iopub.execute_input": "2023-08-22T07:00:15.014465Z", + "iopub.status.busy": "2023-08-22T07:00:15.014315Z", + "iopub.status.idle": "2023-08-22T07:00:15.127942Z", + "shell.execute_reply": "2023-08-22T07:00:15.127535Z" } }, "outputs": [ @@ -9520,10 +9520,10 @@ "id": "b6c30e1c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:32.088803Z", - "iopub.status.busy": "2023-08-21T02:29:32.088665Z", - "iopub.status.idle": "2023-08-21T02:29:32.188991Z", - "shell.execute_reply": "2023-08-21T02:29:32.188578Z" + "iopub.execute_input": "2023-08-22T07:00:15.129800Z", + "iopub.status.busy": "2023-08-22T07:00:15.129659Z", + "iopub.status.idle": "2023-08-22T07:00:15.218853Z", + "shell.execute_reply": "2023-08-22T07:00:15.218439Z" } }, "outputs": [ @@ -9575,10 +9575,10 @@ "id": "6fedf71f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:32.190664Z", - "iopub.status.busy": "2023-08-21T02:29:32.190543Z", - "iopub.status.idle": "2023-08-21T02:29:32.196709Z", - "shell.execute_reply": "2023-08-21T02:29:32.196462Z" + "iopub.execute_input": "2023-08-22T07:00:15.220829Z", + "iopub.status.busy": "2023-08-22T07:00:15.220699Z", + "iopub.status.idle": "2023-08-22T07:00:15.226460Z", + "shell.execute_reply": "2023-08-22T07:00:15.226111Z" }, "lines_to_next_cell": 2 }, @@ -9621,10 +9621,10 @@ "id": "f78e9153", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:32.198160Z", - "iopub.status.busy": "2023-08-21T02:29:32.198072Z", - "iopub.status.idle": "2023-08-21T02:29:32.201083Z", - "shell.execute_reply": "2023-08-21T02:29:32.200686Z" + "iopub.execute_input": "2023-08-22T07:00:15.228509Z", + "iopub.status.busy": "2023-08-22T07:00:15.228362Z", + "iopub.status.idle": "2023-08-22T07:00:15.230933Z", + "shell.execute_reply": "2023-08-22T07:00:15.230633Z" } }, "outputs": [ @@ -9676,10 +9676,10 @@ "id": "31120c88", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:32.203509Z", - "iopub.status.busy": "2023-08-21T02:29:32.203359Z", - "iopub.status.idle": "2023-08-21T02:29:32.207977Z", - "shell.execute_reply": "2023-08-21T02:29:32.207598Z" + "iopub.execute_input": "2023-08-22T07:00:15.232659Z", + "iopub.status.busy": "2023-08-22T07:00:15.232549Z", + "iopub.status.idle": "2023-08-22T07:00:15.235970Z", + "shell.execute_reply": "2023-08-22T07:00:15.235650Z" } }, "outputs": [ @@ -9718,10 +9718,10 @@ "id": "fc6b3a12", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:32.210299Z", - "iopub.status.busy": "2023-08-21T02:29:32.210090Z", - "iopub.status.idle": "2023-08-21T02:29:32.358906Z", - "shell.execute_reply": "2023-08-21T02:29:32.358585Z" + "iopub.execute_input": "2023-08-22T07:00:15.237863Z", + "iopub.status.busy": "2023-08-22T07:00:15.237759Z", + "iopub.status.idle": "2023-08-22T07:00:15.333920Z", + "shell.execute_reply": "2023-08-22T07:00:15.333623Z" } }, "outputs": [ @@ -9771,10 +9771,10 @@ "id": "b806f0e8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:32.362552Z", - "iopub.status.busy": "2023-08-21T02:29:32.362360Z", - "iopub.status.idle": "2023-08-21T02:29:32.464295Z", - "shell.execute_reply": "2023-08-21T02:29:32.463871Z" + "iopub.execute_input": "2023-08-22T07:00:15.335731Z", + "iopub.status.busy": "2023-08-22T07:00:15.335610Z", + "iopub.status.idle": "2023-08-22T07:00:15.425776Z", + "shell.execute_reply": "2023-08-22T07:00:15.425408Z" } }, "outputs": [ @@ -9815,7 +9815,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -9828,7 +9828,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch07-nonlin-lab.Rmd b/Ch07-nonlin-lab.Rmd index c2abf72..c595752 100644 --- a/Ch07-nonlin-lab.Rmd +++ b/Ch07-nonlin-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch07-nonlin-lab.ipynb b/Ch07-nonlin-lab.ipynb index b56a2db..347036d 100644 --- a/Ch07-nonlin-lab.ipynb +++ b/Ch07-nonlin-lab.ipynb @@ -21,10 +21,10 @@ "id": "f0d9a8c8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:33.891853Z", - "iopub.status.busy": "2023-08-21T02:29:33.891740Z", - "iopub.status.idle": "2023-08-21T02:29:35.316371Z", - "shell.execute_reply": "2023-08-21T02:29:35.315923Z" + "iopub.execute_input": "2023-08-22T07:00:19.101721Z", + "iopub.status.busy": "2023-08-22T07:00:19.101624Z", + "iopub.status.idle": "2023-08-22T07:00:20.128515Z", + "shell.execute_reply": "2023-08-22T07:00:20.128166Z" } }, "outputs": [], @@ -55,10 +55,10 @@ "id": "c4bc71b4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.320427Z", - "iopub.status.busy": "2023-08-21T02:29:35.319735Z", - "iopub.status.idle": "2023-08-21T02:29:35.335825Z", - "shell.execute_reply": "2023-08-21T02:29:35.335435Z" + "iopub.execute_input": "2023-08-22T07:00:20.130689Z", + "iopub.status.busy": "2023-08-22T07:00:20.130382Z", + "iopub.status.idle": "2023-08-22T07:00:20.144261Z", + "shell.execute_reply": "2023-08-22T07:00:20.143915Z" } }, "outputs": [], @@ -94,10 +94,10 @@ "id": "14649fd7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.338249Z", - "iopub.status.busy": "2023-08-21T02:29:35.338114Z", - "iopub.status.idle": "2023-08-21T02:29:35.348243Z", - "shell.execute_reply": "2023-08-21T02:29:35.347922Z" + "iopub.execute_input": "2023-08-22T07:00:20.146307Z", + "iopub.status.busy": "2023-08-22T07:00:20.146145Z", + "iopub.status.idle": "2023-08-22T07:00:20.154062Z", + "shell.execute_reply": "2023-08-22T07:00:20.153676Z" } }, "outputs": [], @@ -124,10 +124,10 @@ "id": "bca84aa3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.350246Z", - "iopub.status.busy": "2023-08-21T02:29:35.350053Z", - "iopub.status.idle": "2023-08-21T02:29:35.474010Z", - "shell.execute_reply": "2023-08-21T02:29:35.473145Z" + "iopub.execute_input": "2023-08-22T07:00:20.155897Z", + "iopub.status.busy": "2023-08-22T07:00:20.155777Z", + "iopub.status.idle": "2023-08-22T07:00:20.258666Z", + "shell.execute_reply": "2023-08-22T07:00:20.253837Z" }, "lines_to_next_cell": 2 }, @@ -259,10 +259,10 @@ "id": "411af5ab", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.479757Z", - "iopub.status.busy": "2023-08-21T02:29:35.479078Z", - "iopub.status.idle": "2023-08-21T02:29:35.483997Z", - "shell.execute_reply": "2023-08-21T02:29:35.483275Z" + "iopub.execute_input": "2023-08-22T07:00:20.267608Z", + "iopub.status.busy": "2023-08-22T07:00:20.265087Z", + "iopub.status.idle": "2023-08-22T07:00:20.272250Z", + "shell.execute_reply": "2023-08-22T07:00:20.271081Z" } }, "outputs": [], @@ -294,10 +294,10 @@ "id": "0eb6317c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.487461Z", - "iopub.status.busy": "2023-08-21T02:29:35.487287Z", - "iopub.status.idle": "2023-08-21T02:29:35.493595Z", - "shell.execute_reply": "2023-08-21T02:29:35.491379Z" + "iopub.execute_input": "2023-08-22T07:00:20.278663Z", + "iopub.status.busy": "2023-08-22T07:00:20.278281Z", + "iopub.status.idle": "2023-08-22T07:00:20.286475Z", + "shell.execute_reply": "2023-08-22T07:00:20.285277Z" }, "lines_to_next_cell": 0 }, @@ -351,10 +351,10 @@ "id": "714f2c6d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.499091Z", - "iopub.status.busy": "2023-08-21T02:29:35.498388Z", - "iopub.status.idle": "2023-08-21T02:29:35.798204Z", - "shell.execute_reply": "2023-08-21T02:29:35.797853Z" + "iopub.execute_input": "2023-08-22T07:00:20.291120Z", + "iopub.status.busy": "2023-08-22T07:00:20.289650Z", + "iopub.status.idle": "2023-08-22T07:00:20.490780Z", + "shell.execute_reply": "2023-08-22T07:00:20.489475Z" }, "lines_to_next_cell": 0 }, @@ -420,10 +420,10 @@ "id": "0f5f60ed", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.799903Z", - "iopub.status.busy": "2023-08-21T02:29:35.799807Z", - "iopub.status.idle": "2023-08-21T02:29:35.885877Z", - "shell.execute_reply": "2023-08-21T02:29:35.880532Z" + "iopub.execute_input": "2023-08-22T07:00:20.501016Z", + "iopub.status.busy": "2023-08-22T07:00:20.500451Z", + "iopub.status.idle": "2023-08-22T07:00:20.542279Z", + "shell.execute_reply": "2023-08-22T07:00:20.541055Z" } }, "outputs": [ @@ -560,10 +560,10 @@ "id": "3ca7417d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.892132Z", - "iopub.status.busy": "2023-08-21T02:29:35.891945Z", - "iopub.status.idle": "2023-08-21T02:29:35.906237Z", - "shell.execute_reply": "2023-08-21T02:29:35.903796Z" + "iopub.execute_input": "2023-08-22T07:00:20.547883Z", + "iopub.status.busy": "2023-08-22T07:00:20.546804Z", + "iopub.status.idle": "2023-08-22T07:00:20.558851Z", + "shell.execute_reply": "2023-08-22T07:00:20.557712Z" }, "lines_to_next_cell": 2 }, @@ -669,10 +669,10 @@ "id": "caadfcc3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.910461Z", - "iopub.status.busy": "2023-08-21T02:29:35.909732Z", - "iopub.status.idle": "2023-08-21T02:29:35.916845Z", - "shell.execute_reply": "2023-08-21T02:29:35.914913Z" + "iopub.execute_input": "2023-08-22T07:00:20.563550Z", + "iopub.status.busy": "2023-08-22T07:00:20.562723Z", + "iopub.status.idle": "2023-08-22T07:00:20.568989Z", + "shell.execute_reply": "2023-08-22T07:00:20.568096Z" }, "lines_to_next_cell": 2 }, @@ -710,10 +710,10 @@ "id": "92de2600", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.921712Z", - "iopub.status.busy": "2023-08-21T02:29:35.921332Z", - "iopub.status.idle": "2023-08-21T02:29:35.972191Z", - "shell.execute_reply": "2023-08-21T02:29:35.968927Z" + "iopub.execute_input": "2023-08-22T07:00:20.574149Z", + "iopub.status.busy": "2023-08-22T07:00:20.573276Z", + "iopub.status.idle": "2023-08-22T07:00:20.605121Z", + "shell.execute_reply": "2023-08-22T07:00:20.604136Z" }, "lines_to_next_cell": 2 }, @@ -820,10 +820,10 @@ "id": "a4452162", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:35.977098Z", - "iopub.status.busy": "2023-08-21T02:29:35.976606Z", - "iopub.status.idle": "2023-08-21T02:29:36.071648Z", - "shell.execute_reply": "2023-08-21T02:29:36.069969Z" + "iopub.execute_input": "2023-08-22T07:00:20.609844Z", + "iopub.status.busy": "2023-08-22T07:00:20.609519Z", + "iopub.status.idle": "2023-08-22T07:00:20.635472Z", + "shell.execute_reply": "2023-08-22T07:00:20.634538Z" }, "lines_to_next_cell": 2 }, @@ -933,10 +933,10 @@ "id": "5b317cb2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.079783Z", - "iopub.status.busy": "2023-08-21T02:29:36.079376Z", - "iopub.status.idle": "2023-08-21T02:29:36.089301Z", - "shell.execute_reply": "2023-08-21T02:29:36.086171Z" + "iopub.execute_input": "2023-08-22T07:00:20.644474Z", + "iopub.status.busy": "2023-08-22T07:00:20.644125Z", + "iopub.status.idle": "2023-08-22T07:00:20.652869Z", + "shell.execute_reply": "2023-08-22T07:00:20.652118Z" } }, "outputs": [], @@ -960,10 +960,10 @@ "id": "ba682884", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.096542Z", - "iopub.status.busy": "2023-08-21T02:29:36.096230Z", - "iopub.status.idle": "2023-08-21T02:29:36.294776Z", - "shell.execute_reply": "2023-08-21T02:29:36.292034Z" + "iopub.execute_input": "2023-08-22T07:00:20.659807Z", + "iopub.status.busy": "2023-08-22T07:00:20.659436Z", + "iopub.status.idle": "2023-08-22T07:00:20.794764Z", + "shell.execute_reply": "2023-08-22T07:00:20.793804Z" }, "lines_to_next_cell": 0 }, @@ -1025,10 +1025,10 @@ "id": "84c211b3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.301026Z", - "iopub.status.busy": "2023-08-21T02:29:36.300636Z", - "iopub.status.idle": "2023-08-21T02:29:36.330683Z", - "shell.execute_reply": "2023-08-21T02:29:36.329634Z" + "iopub.execute_input": "2023-08-22T07:00:20.802014Z", + "iopub.status.busy": "2023-08-22T07:00:20.801524Z", + "iopub.status.idle": "2023-08-22T07:00:20.820547Z", + "shell.execute_reply": "2023-08-22T07:00:20.819213Z" }, "lines_to_next_cell": 2 }, @@ -1154,10 +1154,10 @@ "id": "60466a94", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.335194Z", - "iopub.status.busy": "2023-08-21T02:29:36.334390Z", - "iopub.status.idle": "2023-08-21T02:29:36.342883Z", - "shell.execute_reply": "2023-08-21T02:29:36.341853Z" + "iopub.execute_input": "2023-08-22T07:00:20.827052Z", + "iopub.status.busy": "2023-08-22T07:00:20.826622Z", + "iopub.status.idle": "2023-08-22T07:00:20.840226Z", + "shell.execute_reply": "2023-08-22T07:00:20.838401Z" }, "lines_to_next_cell": 0 }, @@ -1197,10 +1197,10 @@ "id": "ff6d9fcb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.348667Z", - "iopub.status.busy": "2023-08-21T02:29:36.347888Z", - "iopub.status.idle": "2023-08-21T02:29:36.376193Z", - "shell.execute_reply": "2023-08-21T02:29:36.375375Z" + "iopub.execute_input": "2023-08-22T07:00:20.847470Z", + "iopub.status.busy": "2023-08-22T07:00:20.846698Z", + "iopub.status.idle": "2023-08-22T07:00:20.876785Z", + "shell.execute_reply": "2023-08-22T07:00:20.874921Z" }, "lines_to_next_cell": 0 }, @@ -1323,10 +1323,10 @@ "id": "2a206718", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.386789Z", - "iopub.status.busy": "2023-08-21T02:29:36.386044Z", - "iopub.status.idle": "2023-08-21T02:29:36.418061Z", - "shell.execute_reply": "2023-08-21T02:29:36.416433Z" + "iopub.execute_input": "2023-08-22T07:00:20.884203Z", + "iopub.status.busy": "2023-08-22T07:00:20.883987Z", + "iopub.status.idle": "2023-08-22T07:00:20.912686Z", + "shell.execute_reply": "2023-08-22T07:00:20.910961Z" } }, "outputs": [ @@ -1459,10 +1459,10 @@ "id": "766241f2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.425365Z", - "iopub.status.busy": "2023-08-21T02:29:36.424580Z", - "iopub.status.idle": "2023-08-21T02:29:36.432225Z", - "shell.execute_reply": "2023-08-21T02:29:36.431397Z" + "iopub.execute_input": "2023-08-22T07:00:20.920607Z", + "iopub.status.busy": "2023-08-22T07:00:20.918963Z", + "iopub.status.idle": "2023-08-22T07:00:20.929300Z", + "shell.execute_reply": "2023-08-22T07:00:20.928186Z" }, "lines_to_next_cell": 0 }, @@ -1504,10 +1504,10 @@ "id": "71b3ac84", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.443753Z", - "iopub.status.busy": "2023-08-21T02:29:36.443393Z", - "iopub.status.idle": "2023-08-21T02:29:36.490069Z", - "shell.execute_reply": "2023-08-21T02:29:36.489170Z" + "iopub.execute_input": "2023-08-22T07:00:20.943822Z", + "iopub.status.busy": "2023-08-22T07:00:20.943014Z", + "iopub.status.idle": "2023-08-22T07:00:20.968025Z", + "shell.execute_reply": "2023-08-22T07:00:20.966003Z" }, "lines_to_next_cell": 0 }, @@ -1638,10 +1638,10 @@ "id": "eb35ef98", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.498313Z", - "iopub.status.busy": "2023-08-21T02:29:36.498133Z", - "iopub.status.idle": "2023-08-21T02:29:36.532175Z", - "shell.execute_reply": "2023-08-21T02:29:36.530924Z" + "iopub.execute_input": "2023-08-22T07:00:20.975032Z", + "iopub.status.busy": "2023-08-22T07:00:20.974773Z", + "iopub.status.idle": "2023-08-22T07:00:21.001621Z", + "shell.execute_reply": "2023-08-22T07:00:20.999410Z" }, "lines_to_next_cell": 0 }, @@ -1755,10 +1755,10 @@ "id": "78b393fe", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.541740Z", - "iopub.status.busy": "2023-08-21T02:29:36.541236Z", - "iopub.status.idle": "2023-08-21T02:29:36.729893Z", - "shell.execute_reply": "2023-08-21T02:29:36.728852Z" + "iopub.execute_input": "2023-08-22T07:00:21.009111Z", + "iopub.status.busy": "2023-08-22T07:00:21.008401Z", + "iopub.status.idle": "2023-08-22T07:00:21.127979Z", + "shell.execute_reply": "2023-08-22T07:00:21.126680Z" } }, "outputs": [ @@ -1803,10 +1803,10 @@ "id": "cb014cc6", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.738629Z", - "iopub.status.busy": "2023-08-21T02:29:36.738138Z", - "iopub.status.idle": "2023-08-21T02:29:36.783309Z", - "shell.execute_reply": "2023-08-21T02:29:36.781945Z" + "iopub.execute_input": "2023-08-22T07:00:21.135155Z", + "iopub.status.busy": "2023-08-22T07:00:21.134355Z", + "iopub.status.idle": "2023-08-22T07:00:21.153025Z", + "shell.execute_reply": "2023-08-22T07:00:21.152246Z" } }, "outputs": [ @@ -1849,10 +1849,10 @@ "id": "106dc178", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:36.791911Z", - "iopub.status.busy": "2023-08-21T02:29:36.791104Z", - "iopub.status.idle": "2023-08-21T02:29:37.275891Z", - "shell.execute_reply": "2023-08-21T02:29:37.275551Z" + "iopub.execute_input": "2023-08-22T07:00:21.159707Z", + "iopub.status.busy": "2023-08-22T07:00:21.159506Z", + "iopub.status.idle": "2023-08-22T07:00:21.446559Z", + "shell.execute_reply": "2023-08-22T07:00:21.445625Z" } }, "outputs": [ @@ -1895,10 +1895,10 @@ "id": "d0334df0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:37.277695Z", - "iopub.status.busy": "2023-08-21T02:29:37.277558Z", - "iopub.status.idle": "2023-08-21T02:29:38.159528Z", - "shell.execute_reply": "2023-08-21T02:29:38.158089Z" + "iopub.execute_input": "2023-08-22T07:00:21.454580Z", + "iopub.status.busy": "2023-08-22T07:00:21.453805Z", + "iopub.status.idle": "2023-08-22T07:00:21.741596Z", + "shell.execute_reply": "2023-08-22T07:00:21.740381Z" } }, "outputs": [ @@ -1950,10 +1950,10 @@ "id": "e00ec554", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:38.167367Z", - "iopub.status.busy": "2023-08-21T02:29:38.166718Z", - "iopub.status.idle": "2023-08-21T02:29:38.206501Z", - "shell.execute_reply": "2023-08-21T02:29:38.203694Z" + "iopub.execute_input": "2023-08-22T07:00:21.748135Z", + "iopub.status.busy": "2023-08-22T07:00:21.747093Z", + "iopub.status.idle": "2023-08-22T07:00:21.771304Z", + "shell.execute_reply": "2023-08-22T07:00:21.768895Z" }, "lines_to_next_cell": 2 }, @@ -1992,10 +1992,10 @@ "id": "28e301a2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:38.216727Z", - "iopub.status.busy": "2023-08-21T02:29:38.215858Z", - "iopub.status.idle": "2023-08-21T02:29:38.814109Z", - "shell.execute_reply": "2023-08-21T02:29:38.813789Z" + "iopub.execute_input": "2023-08-22T07:00:21.776636Z", + "iopub.status.busy": "2023-08-22T07:00:21.775975Z", + "iopub.status.idle": "2023-08-22T07:00:22.088656Z", + "shell.execute_reply": "2023-08-22T07:00:22.087101Z" } }, "outputs": [ @@ -2054,10 +2054,10 @@ "id": "7988af75", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:38.815771Z", - "iopub.status.busy": "2023-08-21T02:29:38.815666Z", - "iopub.status.idle": "2023-08-21T02:29:38.846626Z", - "shell.execute_reply": "2023-08-21T02:29:38.845296Z" + "iopub.execute_input": "2023-08-22T07:00:22.093999Z", + "iopub.status.busy": "2023-08-22T07:00:22.092990Z", + "iopub.status.idle": "2023-08-22T07:00:22.104732Z", + "shell.execute_reply": "2023-08-22T07:00:22.103894Z" }, "lines_to_next_cell": 0 }, @@ -2093,10 +2093,10 @@ "id": "1a4803f3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:38.852512Z", - "iopub.status.busy": "2023-08-21T02:29:38.851848Z", - "iopub.status.idle": "2023-08-21T02:29:39.089982Z", - "shell.execute_reply": "2023-08-21T02:29:39.089296Z" + "iopub.execute_input": "2023-08-22T07:00:22.111630Z", + "iopub.status.busy": "2023-08-22T07:00:22.109538Z", + "iopub.status.idle": "2023-08-22T07:00:22.238185Z", + "shell.execute_reply": "2023-08-22T07:00:22.237011Z" }, "lines_to_next_cell": 0 }, @@ -2156,10 +2156,10 @@ "id": "dc655431", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.094771Z", - "iopub.status.busy": "2023-08-21T02:29:39.093629Z", - "iopub.status.idle": "2023-08-21T02:29:39.227174Z", - "shell.execute_reply": "2023-08-21T02:29:39.226787Z" + "iopub.execute_input": "2023-08-22T07:00:22.242955Z", + "iopub.status.busy": "2023-08-22T07:00:22.242470Z", + "iopub.status.idle": "2023-08-22T07:00:22.377106Z", + "shell.execute_reply": "2023-08-22T07:00:22.375348Z" } }, "outputs": [ @@ -2217,10 +2217,10 @@ "id": "90ea4ff0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.228985Z", - "iopub.status.busy": "2023-08-21T02:29:39.228844Z", - "iopub.status.idle": "2023-08-21T02:29:39.289822Z", - "shell.execute_reply": "2023-08-21T02:29:39.286542Z" + "iopub.execute_input": "2023-08-22T07:00:22.382764Z", + "iopub.status.busy": "2023-08-22T07:00:22.381824Z", + "iopub.status.idle": "2023-08-22T07:00:22.403585Z", + "shell.execute_reply": "2023-08-22T07:00:22.401813Z" }, "lines_to_next_cell": 0 }, @@ -2254,10 +2254,10 @@ "id": "104bc542", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.297216Z", - "iopub.status.busy": "2023-08-21T02:29:39.295538Z", - "iopub.status.idle": "2023-08-21T02:29:39.509987Z", - "shell.execute_reply": "2023-08-21T02:29:39.505606Z" + "iopub.execute_input": "2023-08-22T07:00:22.408939Z", + "iopub.status.busy": "2023-08-22T07:00:22.408540Z", + "iopub.status.idle": "2023-08-22T07:00:22.524209Z", + "shell.execute_reply": "2023-08-22T07:00:22.522972Z" } }, "outputs": [ @@ -2297,10 +2297,10 @@ "id": "d5884f39", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.515536Z", - "iopub.status.busy": "2023-08-21T02:29:39.514906Z", - "iopub.status.idle": "2023-08-21T02:29:39.590528Z", - "shell.execute_reply": "2023-08-21T02:29:39.587475Z" + "iopub.execute_input": "2023-08-22T07:00:22.529074Z", + "iopub.status.busy": "2023-08-22T07:00:22.528274Z", + "iopub.status.idle": "2023-08-22T07:00:22.562860Z", + "shell.execute_reply": "2023-08-22T07:00:22.561973Z" }, "lines_to_next_cell": 0 }, @@ -2330,10 +2330,10 @@ "id": "9155767c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.595864Z", - "iopub.status.busy": "2023-08-21T02:29:39.595093Z", - "iopub.status.idle": "2023-08-21T02:29:39.751046Z", - "shell.execute_reply": "2023-08-21T02:29:39.747430Z" + "iopub.execute_input": "2023-08-22T07:00:22.569210Z", + "iopub.status.busy": "2023-08-22T07:00:22.568849Z", + "iopub.status.idle": "2023-08-22T07:00:22.677881Z", + "shell.execute_reply": "2023-08-22T07:00:22.676932Z" }, "lines_to_next_cell": 0 }, @@ -2383,10 +2383,10 @@ "id": "048524d1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.765191Z", - "iopub.status.busy": "2023-08-21T02:29:39.764636Z", - "iopub.status.idle": "2023-08-21T02:29:39.875769Z", - "shell.execute_reply": "2023-08-21T02:29:39.875407Z" + "iopub.execute_input": "2023-08-22T07:00:22.685366Z", + "iopub.status.busy": "2023-08-22T07:00:22.684753Z", + "iopub.status.idle": "2023-08-22T07:00:22.790525Z", + "shell.execute_reply": "2023-08-22T07:00:22.789666Z" } }, "outputs": [ @@ -2430,10 +2430,10 @@ "id": "3d632d24", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:39.878255Z", - "iopub.status.busy": "2023-08-21T02:29:39.878128Z", - "iopub.status.idle": "2023-08-21T02:29:40.030675Z", - "shell.execute_reply": "2023-08-21T02:29:40.030077Z" + "iopub.execute_input": "2023-08-22T07:00:22.797262Z", + "iopub.status.busy": "2023-08-22T07:00:22.796333Z", + "iopub.status.idle": "2023-08-22T07:00:22.839603Z", + "shell.execute_reply": "2023-08-22T07:00:22.837625Z" } }, "outputs": [ @@ -2477,10 +2477,10 @@ "id": "f5e21a13", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:40.036373Z", - "iopub.status.busy": "2023-08-21T02:29:40.035626Z", - "iopub.status.idle": "2023-08-21T02:29:40.048244Z", - "shell.execute_reply": "2023-08-21T02:29:40.047103Z" + "iopub.execute_input": "2023-08-22T07:00:22.850660Z", + "iopub.status.busy": "2023-08-22T07:00:22.849974Z", + "iopub.status.idle": "2023-08-22T07:00:22.858653Z", + "shell.execute_reply": "2023-08-22T07:00:22.857543Z" }, "lines_to_next_cell": 0 }, @@ -2584,10 +2584,10 @@ "id": "6bc84bd9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:40.053032Z", - "iopub.status.busy": "2023-08-21T02:29:40.052718Z", - "iopub.status.idle": "2023-08-21T02:29:40.121414Z", - "shell.execute_reply": "2023-08-21T02:29:40.119305Z" + "iopub.execute_input": "2023-08-22T07:00:22.866946Z", + "iopub.status.busy": "2023-08-22T07:00:22.866205Z", + "iopub.status.idle": "2023-08-22T07:00:22.902537Z", + "shell.execute_reply": "2023-08-22T07:00:22.901746Z" } }, "outputs": [ @@ -2694,10 +2694,10 @@ "id": "dd9e0491", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:40.127853Z", - "iopub.status.busy": "2023-08-21T02:29:40.126917Z", - "iopub.status.idle": "2023-08-21T02:29:40.134348Z", - "shell.execute_reply": "2023-08-21T02:29:40.133225Z" + "iopub.execute_input": "2023-08-22T07:00:22.910365Z", + "iopub.status.busy": "2023-08-22T07:00:22.909672Z", + "iopub.status.idle": "2023-08-22T07:00:22.916982Z", + "shell.execute_reply": "2023-08-22T07:00:22.915954Z" } }, "outputs": [ @@ -2736,7 +2736,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_81087/2135516388.py:1: UserWarning: KNOWN BUG: p-values computed in this summary are likely much smaller than they should be. \n", + "/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_84754/2135516388.py:1: UserWarning: KNOWN BUG: p-values computed in this summary are likely much smaller than they should be. \n", " \n", "Please do not make inferences based on these values! \n", "\n", @@ -2767,10 +2767,10 @@ "id": "cb3cb4ef", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:40.140991Z", - "iopub.status.busy": "2023-08-21T02:29:40.139059Z", - "iopub.status.idle": "2023-08-21T02:29:40.156398Z", - "shell.execute_reply": "2023-08-21T02:29:40.154898Z" + "iopub.execute_input": "2023-08-22T07:00:22.924618Z", + "iopub.status.busy": "2023-08-22T07:00:22.924291Z", + "iopub.status.idle": "2023-08-22T07:00:22.938562Z", + "shell.execute_reply": "2023-08-22T07:00:22.937364Z" } }, "outputs": [], @@ -2793,10 +2793,10 @@ "id": "583711cb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:40.161933Z", - "iopub.status.busy": "2023-08-21T02:29:40.161044Z", - "iopub.status.idle": "2023-08-21T02:29:41.074609Z", - "shell.execute_reply": "2023-08-21T02:29:41.073657Z" + "iopub.execute_input": "2023-08-22T07:00:22.946138Z", + "iopub.status.busy": "2023-08-22T07:00:22.945678Z", + "iopub.status.idle": "2023-08-22T07:00:23.056404Z", + "shell.execute_reply": "2023-08-22T07:00:23.054342Z" }, "lines_to_next_cell": 2 }, @@ -2827,10 +2827,10 @@ "id": "259d273b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.077991Z", - "iopub.status.busy": "2023-08-21T02:29:41.077451Z", - "iopub.status.idle": "2023-08-21T02:29:41.210787Z", - "shell.execute_reply": "2023-08-21T02:29:41.209817Z" + "iopub.execute_input": "2023-08-22T07:00:23.062645Z", + "iopub.status.busy": "2023-08-22T07:00:23.062312Z", + "iopub.status.idle": "2023-08-22T07:00:23.191981Z", + "shell.execute_reply": "2023-08-22T07:00:23.190477Z" }, "lines_to_next_cell": 0 }, @@ -2871,10 +2871,10 @@ "id": "71dde739", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.214250Z", - "iopub.status.busy": "2023-08-21T02:29:41.213993Z", - "iopub.status.idle": "2023-08-21T02:29:41.230586Z", - "shell.execute_reply": "2023-08-21T02:29:41.229987Z" + "iopub.execute_input": "2023-08-22T07:00:23.199542Z", + "iopub.status.busy": "2023-08-22T07:00:23.199201Z", + "iopub.status.idle": "2023-08-22T07:00:23.217281Z", + "shell.execute_reply": "2023-08-22T07:00:23.216211Z" }, "lines_to_next_cell": 0 }, @@ -2980,10 +2980,10 @@ "id": "126b4433", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.236028Z", - "iopub.status.busy": "2023-08-21T02:29:41.234087Z", - "iopub.status.idle": "2023-08-21T02:29:41.242018Z", - "shell.execute_reply": "2023-08-21T02:29:41.240913Z" + "iopub.execute_input": "2023-08-22T07:00:23.225140Z", + "iopub.status.busy": "2023-08-22T07:00:23.224675Z", + "iopub.status.idle": "2023-08-22T07:00:23.231622Z", + "shell.execute_reply": "2023-08-22T07:00:23.230728Z" }, "lines_to_next_cell": 0 }, @@ -3014,10 +3014,10 @@ "id": "71357343", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.246132Z", - "iopub.status.busy": "2023-08-21T02:29:41.245849Z", - "iopub.status.idle": "2023-08-21T02:29:41.516225Z", - "shell.execute_reply": "2023-08-21T02:29:41.513222Z" + "iopub.execute_input": "2023-08-22T07:00:23.238285Z", + "iopub.status.busy": "2023-08-22T07:00:23.237444Z", + "iopub.status.idle": "2023-08-22T07:00:23.300732Z", + "shell.execute_reply": "2023-08-22T07:00:23.299079Z" }, "lines_to_next_cell": 2 }, @@ -3057,10 +3057,10 @@ "id": "568fe30f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.521913Z", - "iopub.status.busy": "2023-08-21T02:29:41.521643Z", - "iopub.status.idle": "2023-08-21T02:29:41.650531Z", - "shell.execute_reply": "2023-08-21T02:29:41.648645Z" + "iopub.execute_input": "2023-08-22T07:00:23.308132Z", + "iopub.status.busy": "2023-08-22T07:00:23.307471Z", + "iopub.status.idle": "2023-08-22T07:00:23.412833Z", + "shell.execute_reply": "2023-08-22T07:00:23.411958Z" } }, "outputs": [ @@ -3091,10 +3091,10 @@ "id": "56f3acef", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.656894Z", - "iopub.status.busy": "2023-08-21T02:29:41.656175Z", - "iopub.status.idle": "2023-08-21T02:29:41.778189Z", - "shell.execute_reply": "2023-08-21T02:29:41.777902Z" + "iopub.execute_input": "2023-08-22T07:00:23.419875Z", + "iopub.status.busy": "2023-08-22T07:00:23.419189Z", + "iopub.status.idle": "2023-08-22T07:00:23.528901Z", + "shell.execute_reply": "2023-08-22T07:00:23.527531Z" } }, "outputs": [ @@ -3124,10 +3124,10 @@ "id": "74d23615", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.779880Z", - "iopub.status.busy": "2023-08-21T02:29:41.779764Z", - "iopub.status.idle": "2023-08-21T02:29:41.891093Z", - "shell.execute_reply": "2023-08-21T02:29:41.890788Z" + "iopub.execute_input": "2023-08-22T07:00:23.533975Z", + "iopub.status.busy": "2023-08-22T07:00:23.533655Z", + "iopub.status.idle": "2023-08-22T07:00:23.643883Z", + "shell.execute_reply": "2023-08-22T07:00:23.643400Z" }, "lines_to_next_cell": 2 }, @@ -3172,10 +3172,10 @@ "id": "5a0046bf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:41.892708Z", - "iopub.status.busy": "2023-08-21T02:29:41.892590Z", - "iopub.status.idle": "2023-08-21T02:29:42.034991Z", - "shell.execute_reply": "2023-08-21T02:29:42.034633Z" + "iopub.execute_input": "2023-08-22T07:00:23.646013Z", + "iopub.status.busy": "2023-08-22T07:00:23.645883Z", + "iopub.status.idle": "2023-08-22T07:00:23.774046Z", + "shell.execute_reply": "2023-08-22T07:00:23.773509Z" }, "lines_to_next_cell": 0 }, @@ -3222,7 +3222,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -3235,7 +3235,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch08-baggboost-lab.Rmd b/Ch08-baggboost-lab.Rmd index 50e480c..67a23d6 100644 --- a/Ch08-baggboost-lab.Rmd +++ b/Ch08-baggboost-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch08-baggboost-lab.ipynb b/Ch08-baggboost-lab.ipynb index 0aaa6ac..b378a78 100644 --- a/Ch08-baggboost-lab.ipynb +++ b/Ch08-baggboost-lab.ipynb @@ -26,10 +26,10 @@ "id": "5061d7d5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:43.521031Z", - "iopub.status.busy": "2023-08-21T02:29:43.520759Z", - "iopub.status.idle": "2023-08-21T02:29:44.874525Z", - "shell.execute_reply": "2023-08-21T02:29:44.874222Z" + "iopub.execute_input": "2023-08-22T07:00:27.086529Z", + "iopub.status.busy": "2023-08-22T07:00:27.086444Z", + "iopub.status.idle": "2023-08-22T07:00:28.125805Z", + "shell.execute_reply": "2023-08-22T07:00:28.125477Z" }, "lines_to_next_cell": 0 }, @@ -58,10 +58,10 @@ "id": "747b056a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.876483Z", - "iopub.status.busy": "2023-08-21T02:29:44.876317Z", - "iopub.status.idle": "2023-08-21T02:29:44.941466Z", - "shell.execute_reply": "2023-08-21T02:29:44.941148Z" + "iopub.execute_input": "2023-08-22T07:00:28.127941Z", + "iopub.status.busy": "2023-08-22T07:00:28.127762Z", + "iopub.status.idle": "2023-08-22T07:00:28.677332Z", + "shell.execute_reply": "2023-08-22T07:00:28.676967Z" }, "lines_to_next_cell": 2 }, @@ -106,10 +106,10 @@ "id": "a29167fd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.943319Z", - "iopub.status.busy": "2023-08-21T02:29:44.943207Z", - "iopub.status.idle": "2023-08-21T02:29:44.948609Z", - "shell.execute_reply": "2023-08-21T02:29:44.948363Z" + "iopub.execute_input": "2023-08-22T07:00:28.679410Z", + "iopub.status.busy": "2023-08-22T07:00:28.679295Z", + "iopub.status.idle": "2023-08-22T07:00:28.684543Z", + "shell.execute_reply": "2023-08-22T07:00:28.684233Z" } }, "outputs": [], @@ -137,10 +137,10 @@ "id": "9fc6c8b9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.950122Z", - "iopub.status.busy": "2023-08-21T02:29:44.950017Z", - "iopub.status.idle": "2023-08-21T02:29:44.964042Z", - "shell.execute_reply": "2023-08-21T02:29:44.963794Z" + "iopub.execute_input": "2023-08-22T07:00:28.686277Z", + "iopub.status.busy": "2023-08-22T07:00:28.686146Z", + "iopub.status.idle": "2023-08-22T07:00:28.699975Z", + "shell.execute_reply": "2023-08-22T07:00:28.699627Z" }, "lines_to_next_cell": 0 }, @@ -172,10 +172,10 @@ "id": "533f0949", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.965639Z", - "iopub.status.busy": "2023-08-21T02:29:44.965555Z", - "iopub.status.idle": "2023-08-21T02:29:44.972079Z", - "shell.execute_reply": "2023-08-21T02:29:44.971812Z" + "iopub.execute_input": "2023-08-22T07:00:28.702236Z", + "iopub.status.busy": "2023-08-22T07:00:28.702106Z", + "iopub.status.idle": "2023-08-22T07:00:28.707600Z", + "shell.execute_reply": "2023-08-22T07:00:28.707288Z" }, "lines_to_next_cell": 2 }, @@ -224,10 +224,10 @@ "id": "c4a8718e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.973649Z", - "iopub.status.busy": "2023-08-21T02:29:44.973541Z", - "iopub.status.idle": "2023-08-21T02:29:44.976459Z", - "shell.execute_reply": "2023-08-21T02:29:44.976196Z" + "iopub.execute_input": "2023-08-22T07:00:28.709124Z", + "iopub.status.busy": "2023-08-22T07:00:28.709024Z", + "iopub.status.idle": "2023-08-22T07:00:28.711727Z", + "shell.execute_reply": "2023-08-22T07:00:28.711484Z" }, "lines_to_next_cell": 2 }, @@ -271,10 +271,10 @@ "id": "2fe92cb1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.977909Z", - "iopub.status.busy": "2023-08-21T02:29:44.977813Z", - "iopub.status.idle": "2023-08-21T02:29:44.980904Z", - "shell.execute_reply": "2023-08-21T02:29:44.980648Z" + "iopub.execute_input": "2023-08-22T07:00:28.713483Z", + "iopub.status.busy": "2023-08-22T07:00:28.713358Z", + "iopub.status.idle": "2023-08-22T07:00:28.716712Z", + "shell.execute_reply": "2023-08-22T07:00:28.716377Z" } }, "outputs": [ @@ -314,10 +314,10 @@ "id": "823745dc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:44.982460Z", - "iopub.status.busy": "2023-08-21T02:29:44.982347Z", - "iopub.status.idle": "2023-08-21T02:29:45.271601Z", - "shell.execute_reply": "2023-08-21T02:29:45.271198Z" + "iopub.execute_input": "2023-08-22T07:00:28.718214Z", + "iopub.status.busy": "2023-08-22T07:00:28.718128Z", + "iopub.status.idle": "2023-08-22T07:00:28.972065Z", + "shell.execute_reply": "2023-08-22T07:00:28.971661Z" }, "lines_to_next_cell": 0 }, @@ -362,10 +362,10 @@ "id": "38ec5f13", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.273437Z", - "iopub.status.busy": "2023-08-21T02:29:45.273325Z", - "iopub.status.idle": "2023-08-21T02:29:45.276242Z", - "shell.execute_reply": "2023-08-21T02:29:45.275887Z" + "iopub.execute_input": "2023-08-22T07:00:28.974012Z", + "iopub.status.busy": "2023-08-22T07:00:28.973872Z", + "iopub.status.idle": "2023-08-22T07:00:28.976664Z", + "shell.execute_reply": "2023-08-22T07:00:28.976277Z" } }, "outputs": [ @@ -427,10 +427,10 @@ "id": "3959f39a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.277931Z", - "iopub.status.busy": "2023-08-21T02:29:45.277817Z", - "iopub.status.idle": "2023-08-21T02:29:45.284043Z", - "shell.execute_reply": "2023-08-21T02:29:45.283649Z" + "iopub.execute_input": "2023-08-22T07:00:28.978468Z", + "iopub.status.busy": "2023-08-22T07:00:28.978343Z", + "iopub.status.idle": "2023-08-22T07:00:28.984086Z", + "shell.execute_reply": "2023-08-22T07:00:28.983816Z" }, "lines_to_next_cell": 0 }, @@ -483,10 +483,10 @@ "id": "201c4690", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.286011Z", - "iopub.status.busy": "2023-08-21T02:29:45.285866Z", - "iopub.status.idle": "2023-08-21T02:29:45.288396Z", - "shell.execute_reply": "2023-08-21T02:29:45.288038Z" + "iopub.execute_input": "2023-08-22T07:00:28.986102Z", + "iopub.status.busy": "2023-08-22T07:00:28.985936Z", + "iopub.status.idle": "2023-08-22T07:00:28.988314Z", + "shell.execute_reply": "2023-08-22T07:00:28.988003Z" }, "lines_to_next_cell": 0 }, @@ -516,10 +516,10 @@ "id": "a8dc5c3a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.290090Z", - "iopub.status.busy": "2023-08-21T02:29:45.289979Z", - "iopub.status.idle": "2023-08-21T02:29:45.293957Z", - "shell.execute_reply": "2023-08-21T02:29:45.293696Z" + "iopub.execute_input": "2023-08-22T07:00:28.990208Z", + "iopub.status.busy": "2023-08-22T07:00:28.990083Z", + "iopub.status.idle": "2023-08-22T07:00:28.994160Z", + "shell.execute_reply": "2023-08-22T07:00:28.993813Z" }, "lines_to_next_cell": 0 }, @@ -556,10 +556,10 @@ "id": "0cbe0d28", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.295541Z", - "iopub.status.busy": "2023-08-21T02:29:45.295458Z", - "iopub.status.idle": "2023-08-21T02:29:45.299182Z", - "shell.execute_reply": "2023-08-21T02:29:45.298807Z" + "iopub.execute_input": "2023-08-22T07:00:28.996199Z", + "iopub.status.busy": "2023-08-22T07:00:28.996086Z", + "iopub.status.idle": "2023-08-22T07:00:28.999517Z", + "shell.execute_reply": "2023-08-22T07:00:28.999166Z" }, "lines_to_next_cell": 0 }, @@ -586,10 +586,10 @@ "id": "ea649080", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.300868Z", - "iopub.status.busy": "2023-08-21T02:29:45.300771Z", - "iopub.status.idle": "2023-08-21T02:29:45.571746Z", - "shell.execute_reply": "2023-08-21T02:29:45.571364Z" + "iopub.execute_input": "2023-08-22T07:00:29.001372Z", + "iopub.status.busy": "2023-08-22T07:00:29.001246Z", + "iopub.status.idle": "2023-08-22T07:00:29.236635Z", + "shell.execute_reply": "2023-08-22T07:00:29.236312Z" }, "lines_to_next_cell": 0 }, @@ -629,10 +629,10 @@ "id": "e005da14", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:45.573701Z", - "iopub.status.busy": "2023-08-21T02:29:45.573563Z", - "iopub.status.idle": "2023-08-21T02:29:46.379024Z", - "shell.execute_reply": "2023-08-21T02:29:46.378601Z" + "iopub.execute_input": "2023-08-22T07:00:29.238455Z", + "iopub.status.busy": "2023-08-22T07:00:29.238325Z", + "iopub.status.idle": "2023-08-22T07:00:29.937364Z", + "shell.execute_reply": "2023-08-22T07:00:29.937016Z" }, "lines_to_next_cell": 0 }, @@ -671,10 +671,10 @@ "id": "23324f7e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.381085Z", - "iopub.status.busy": "2023-08-21T02:29:46.380960Z", - "iopub.status.idle": "2023-08-21T02:29:46.383318Z", - "shell.execute_reply": "2023-08-21T02:29:46.383057Z" + "iopub.execute_input": "2023-08-22T07:00:29.939343Z", + "iopub.status.busy": "2023-08-22T07:00:29.939187Z", + "iopub.status.idle": "2023-08-22T07:00:29.942069Z", + "shell.execute_reply": "2023-08-22T07:00:29.941716Z" }, "lines_to_next_cell": 0 }, @@ -711,10 +711,10 @@ "id": "6dcd8b37", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.385077Z", - "iopub.status.busy": "2023-08-21T02:29:46.384936Z", - "iopub.status.idle": "2023-08-21T02:29:46.392841Z", - "shell.execute_reply": "2023-08-21T02:29:46.392541Z" + "iopub.execute_input": "2023-08-22T07:00:29.943944Z", + "iopub.status.busy": "2023-08-22T07:00:29.943797Z", + "iopub.status.idle": "2023-08-22T07:00:29.951177Z", + "shell.execute_reply": "2023-08-22T07:00:29.950818Z" }, "lines_to_next_cell": 2 }, @@ -817,10 +817,10 @@ "id": "0459d3a9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.395016Z", - "iopub.status.busy": "2023-08-21T02:29:46.394693Z", - "iopub.status.idle": "2023-08-21T02:29:46.408492Z", - "shell.execute_reply": "2023-08-21T02:29:46.408187Z" + "iopub.execute_input": "2023-08-22T07:00:29.953197Z", + "iopub.status.busy": "2023-08-22T07:00:29.952962Z", + "iopub.status.idle": "2023-08-22T07:00:29.965364Z", + "shell.execute_reply": "2023-08-22T07:00:29.965021Z" } }, "outputs": [], @@ -847,10 +847,10 @@ "id": "34bf2864", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.411065Z", - "iopub.status.busy": "2023-08-21T02:29:46.410850Z", - "iopub.status.idle": "2023-08-21T02:29:46.413541Z", - "shell.execute_reply": "2023-08-21T02:29:46.413268Z" + "iopub.execute_input": "2023-08-22T07:00:29.967326Z", + "iopub.status.busy": "2023-08-22T07:00:29.967175Z", + "iopub.status.idle": "2023-08-22T07:00:29.969789Z", + "shell.execute_reply": "2023-08-22T07:00:29.969459Z" } }, "outputs": [], @@ -878,16 +878,16 @@ "id": "dd0dfd8a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.415108Z", - "iopub.status.busy": "2023-08-21T02:29:46.414996Z", - "iopub.status.idle": "2023-08-21T02:29:46.704739Z", - "shell.execute_reply": "2023-08-21T02:29:46.704318Z" + "iopub.execute_input": "2023-08-22T07:00:29.971954Z", + "iopub.status.busy": "2023-08-22T07:00:29.971825Z", + "iopub.status.idle": "2023-08-22T07:00:30.219764Z", + "shell.execute_reply": "2023-08-22T07:00:30.219356Z" } }, "outputs": [ { "data": { - "image/png": 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atm2bihUrprlz51qvGz9+vMLCwp44TXrixIkqVKhQckcFACDZUWwBAA4pIiJC5cuXl4+Pj8xmsyIjI7Vt2zb5+PioQoUKql27tu7duydJMpvN6tmzpwICAmQ2mzV//nwFBASoaNGiOnHihPU2Xbp0UeXKleXn56fLly/He7yYmBh16NBBvr6+8vb21q5duyRJI0aMUKlSpeTr6/tK7/2aKlUq68d37txR4cKFrX/u1auXKlSoYH2fX+nR++tu3rz5iV1cAAAcEcUWAOCQQkJCVLlyZYWGhiosLEwZM2ZU8eLFFRoaqu3bt6tgwYJatGiR9faVKlVScHCwPD09tXfvXgUHB6t3796aMWOG9TalS5fWpk2b1KJFC3311VfxHm/69OnKmzevQkJCtHz5cvXq1UuSNG/ePIWGhiokJEQ9evR4Imf9+vVlNpvj/Rf3/rP/NnnyZBUpUkQ7duywFtuvv/5ae/bs0erVq/XNN9/o5MmTkqQvvvhC/fr1e6WvIQAA9oIXjwIAOKTGjRtr5MiRatGihXLmzKnAwEAdOXJEgwcP1v379/X3338rffr01tsXL15ckpQ9e3blzZvX+vHWrVuttylXrpz1/8uXL4/3eIcPH9bOnTu1YcMGSY92TCVpwoQJ6tKlix48eKBPPvlE3t7e8Y57kVdZ7tSpkzp16qRRo0bpq6++0pgxY5Q1a1ZJUsaMGRUQEKCDBw8qZcqUOnv2rCpWrKgzZ84k+P4BALBXFFsAgENycXHRyJEjJUnt2rVTcHCwpk2bps8//1xly5ZV37599fhbuZtMpqd+/Phtdu/eLU9PT+3evVv58+eP93iFCxeWp6enevbsKenRCzdJUtmyZeXn56dz586pXr162r9/f7zj6tevr+vXr8e7zNPTU9OmTYt3WVRUlNzd3SVJmTJlUlRUlKRHBTpjxoyKiYnRjh071KRJEx04cEAXL15U1apVdeHCBd2/f19FihRR3bp1E/4FBADAjlBsAQAOac2aNRo/frxcXV3l5uYmb29v3blzRx999JEKFCig9OnTx9uxTYgDBw5o9uzZevjwoRYsWBDvug4dOqhr167y8fGRJBUrVkxjx45VvXr1FBUVpaioKHXp0uWJ+0zoju3w4cO1c+dOSY/eTzfuFOkmTZrozp07iomJUdOmTfXBBx/ogw8+sP5u7axZs3T+/HlKLQDAoZksjy9FAwCQTA4cOKDixYtr//798vLyMjrOfzKbzQoKClL27NmNjmKT7O37CQBwLLx4FAAAAADArnEqMgAACRAWFmZ0BAAA8Azs2AIAAAAA7BrFFgDg9CIiIuTv759sjxcYGKjSpUurfPny6t69u/WVlz/++GOVKVNGZcqU0ahRo5447ty5c/He7zZlypSKjIy0Xh8eHq6UKVNqx44dkh7tMr/55pvW2+/Zsyd5PkEAAJIZpyIDAJDMmjdvrsDAQEmP3m83JCREfn5+6t27t/Lly6fY2FiVL19ejRo1sr6nriS988471lOid+7cqREjRihTpkzW6wMDA2U2m+M9Vo0aNZ546yAAABwNO7YAAIfUu3dvLV26VJL04MEDvf/++4qJidHAgQPl6+srLy8vTZ48+Ynj2rZtG2/Hs3379pKk33//Xf7+/vL19VWjRo109+7dl86WL18+68dubm5ydXWNd7mLi4tSpEhhvfxp5syZo1atWln/vG3bNuXKlUtvv/12vNtt3LhR3t7e6ty58ytlBgDAllFsAQAOqW3btpo9e7YkKTg4WL6+vkqZMqUGDRqkkJAQ7dq1S+PGjVNMTEyC7q9z586aMWOGQkJCZDabNXXq1HjXR0dHxztNOO6/wYMHP/M+w8LCdP78eVWsWDHe5UFBQcqRI4dy5cr11OOio6O1fv1663vTWiwWjRw5Uv369Yt3u+LFi+vEiRPasWOHsmbNqtGjRyfocwUAwN5wKjIAwCEVKVJEV65c0eXLlzV79mwNGDBAkjR58mStWLFCrq6uunz5si5fvhzvOJPJZP348bd6P3LkiFq3bi1Jun///hOn/KZKleqFXjn5wIEDGjBggNasWSMXl/9bZ16/fr3mzJmjVatWPfPY1atXy9fXV6lTp5YkLVy4UP7+/sqYMWO826VLl876ccuWLdWzZ88E5wMAwJ5QbAEADqtFixaaOHGiIiIiVKxYMUVGRmrmzJk6dOiQYmJilD9//njlVZIyZ86sc+fOSZL27t1rvbxIkSJasGCB3nzzTUmPdk0fFx0drSpVqjyRwdvbWyNGjIh32bFjx/Txxx9rxYoVypIli/Xybdu2acSIEVq3bp3c3d2f+XnNnTtX3bt3t/754MGD2rdvnzZv3qzDhw/r+PHjmj9/vrJkyaIMGTJIkkJCQpQ/f/7nfr0AALBXFFsAgMNq3ry5cuTIoeHDh0uSMmbMqEKFCsnb21uFChWKVyrjtG/fXs2bN9f8+fOVO3du6+UTJ05U27Ztracu9+3bV1WrVrVe/yI7tp06ddKtW7fUsmVLSVKvXr1Uu3ZttW7dWunTp1edOnUkSWPGjFGpUqXUo0cPDRo0SNmyZdO1a9d06NCheDvGj59i3LZtW7Vv31558uTRpEmTNHPmTKVOnVqZM2fWjBkzEvaFAwDAzpgs/16qBgAgGRw4cEDFixfX/v375eXlZXQcvCK+nwAAI/HiUQAAAAAAu0axBQAAAADYNYotAAAAAMCu8eJRAABDHTt2zOgISAR8HwEARqLYAgAMkTVrVnl4eFhfGRj2z8PDQ1mzZjU6BgDACfGqyAAAw5w7d05Xr1415LEPHz6sLl26KG/evBo/frzSpk1rSI5XdefOHXXt2lVnzpzRpEmTVKRIEcOyZM2aVe+8845hjw8AcF4UWwCA09m9e7cCAgL03nvvaf369UqXLp3RkV7J7du3VbVqVf3+++/auHGjSpcubXQkAACSFS8eBQBwKrt27VKVKlX0/vvvO0SplaR06dJpw4YNeu+991S5cmXt2rXL6EgAACQrii0AwGns3LlTVapUUdGiRR2m1MZJly6d1q9fr6JFiyogIEA7d+40OhIAAMmGYgsAcAo///yzAgIC5OXlpXXr1tnt79Q+T7p06bRu3ToVK1ZMAQEB+vnnn42OBABAsqDYAgAc3vbt2xUQEKASJUo4bKmNkzZtWq1du1bFixdX1apVtWPHDqMjAQCQ5Ci2AACHtm3bNlWrVk2lSpXSmjVrlCZNGqMjJbm4cluiRAlVrVpV27dvNzoSAABJimILAHBYW7duVfXq1VW6dGmnKbVx0qRJo7Vr16pUqVKqVq2atm3bZnQkAACSDMUWAOCQwsLCVL16dZUpU0arV6+Wh4eH0ZGSnYeHh9asWaPSpUurWrVq2rp1q9GRAABIEhRbAIDDCQ0NVfXq1VW+fHmnLbVxPDw8tHr1apUrV07Vq1dXWFiY0ZEAAEh0FFsAgEMJCQlRjRo1VKFCBa1cuVKpU6c2OpLhPDw8tGrVKpUvX17Vq1dXSEiI0ZEAAEhUFFsAgMPYvHmzatSooYoVK2rFihWU2sekTp1aK1euVIUKFVSzZk1t2bLF6EgAACQaii0AwCFs2rRJtWrVktlsptQ+Q1y5rVSpkmrWrKnNmzcbHQkAgERBsQUA2L2NGzeqdu3a8vX11fLly+Xu7m50JJvl7u6u5cuXy8fHR7Vq1dKmTZuMjgQAwCuj2AIA7FpwcLBq164tPz8/LVu2jFKbAO7u7lq2bJl8fX1Vq1YtBQcHGx0JAIBXQrEFANitDRs2qE6dOqpcubKWLl0qNzc3oyPZjbhy6+/vrzp16mjDhg1GRwIA4KVRbAEAdmndunWqU6eOqlSpoiVLllBqX4Kbm5uWLl2qKlWqqG7dulq/fr3RkQAAeCkUWwCA3Vm7dq3q1aunatWqUWpfkZubmxYvXqyAgADVrVtX69atMzoSAAAvjGILALAra9asUb169VS9enUtWrRIqVKlMjqS3Ysrt9WqVVO9evW0Zs0aoyMBAPBCKLYAALuxevVq1a9fXzVr1qTUJrJUqVJp0aJFqlGjhurXr6/Vq1cbHQkAgASj2AIA7MLKlSvVoEED1a5dWz/99JNSpkxpdCSHkypVKv3000+qVauWGjRooFWrVhkdCQCABKHYAgBs3ooVK9SwYUPVqVNHCxYsoNQmoZQpU2rhwoWqXbu2GjZsqJUrVxodCQCA/0SxBQDYtOXLl6tRo0aqV6+e5s+fT6lNBilTptSCBQtUt25dNWzYUMuXLzc6EgAAz0WxBQDYrKVLl6px48Zq0KABpTaZpUyZUvPmzVP9+vXVuHFjLVu2zOhIAAA8E8UWAGCTlixZoiZNmqhhw4YKCgpSihQpjI7kdOLKbcOGDdW4cWMtXbrU6EgAADwVxRYAYHMWL16spk2bqkmTJpo7dy6l1kApUqTQ3Llz1bhxYzVp0kSLFy82OhIAAE/gJwUAgE356aef1KJFCzVt2lSzZs2i1NqAFClSaM6cOTKZTGrWrJksFosaN25sdCwAAKz4aQEAYDMWLlyoFi1aqEWLFpo5c6ZcXV2NjoT/L67curi4qHnz5rJYLGrSpInRsQAAkESxBQDYiPnz56tVq1Zq2bKlZsyYQam1Qa6urpo1a5ZMJpOaN2+u2NhYNWvWzOhYAABQbAEAxps3b55at26tVq1aafr06ZRaG+bq6qqZM2fKZDKpZcuWslgsat68udGxAABOjmILADBUUFCQ2rRpozZt2ujHH3+k1NoBV1dXzZgxQy4uLmrVqpViY2PVsmVLo2MBAJwYxRYAYJg5c+aobdu2+vDDD/Xjjz/KxYUX67cXrq6umj59ukwmk9q0aSOLxaJWrVoZHQsA4KQotgAAQ8yePVsffvihPvroI02ZMoVSa4dcXFw0bdo0ubi4qE2bNoqNjVWbNm2MjgUAcEIUWwBAsps5c6Y++ugjtW/fXj/88AOl1o65uLho6tSpMplM+vDDD2WxWNS2bVujYwEAnAzFFgCQrGbMmKH27dvr448/1qRJkyi1DsDFxcW6696uXTtZLBZ9+OGHRscCADgRii0AINlMmzZNHTp00CeffKKJEydSah2Ii4uLJk+eLJPJpI8++kixsbH66KOPjI4FAHASFFsAQLL48ccf9fHHH6tz586aMGGCTCaT0ZGQyFxcXKy78O3bt5fFYlH79u2NjgUAcAIUWwBAkps6dao6duyoLl26aPz48ZRaB+bi4qKJEyfKZDKpQ4cOio2N1ccff2x0LACAg6PYAgCS1A8//KBOnTqpW7du+u677yi1TsBkMmnChAlycXFRx44dZbFY1LFjR6NjAQAcGMUWAJBkJk2apC5duujTTz/VuHHjKLVOxGQy6fvvv5eLi4s++eQTxcbGqlOnTkbHAgA4KIotACBJTJw4UV27dlWPHj00duxYSq0TMplM+vbbb2UymdS5c2dZLBZ17tzZ6FgAAAdEsQUAJLrx48ere/fu6tmzp7755htKrRMzmUzW3fouXbooNjZWXbt2NToWAMDBUGwBAInq+++/16effqrPPvtMX331FaUWMplMGjt2rFxcXNStWzdZLBZ169bN6FgAAAdCsQUAJJpvv/1WPXv2VJ8+fTR69GhKLaxMJpO+/vprubi4qHv37oqNjdWnn35qdCwAgIOg2AIAEsW4cePUq1cv9e3bV6NGjaLU4gkmk0ljxoyRyWRSjx49FBsbq549exodCwDgACi2AIBX9s0336h3797q37+/Ro4cSanFM5lMJo0ePVouLi7q1auXLBaLevXqZXQsAICdo9gCAF7J119/rT59+mjgwIEaMWIEpRb/yWQy6csvv5SLi4s+++wzWSwWffbZZ0bHAgDYMYotAOCljRkzRv369dOgQYP0v//9j1KLBDOZTPriiy9kMpnUu3dvxcbGqk+fPkbHAgDYKYotAOCljB49Wv3799eQIUP0+eefU2rxwkwmk0aMGCEXFxf17dtXFotFffv2NToWAMAOUWwBAC/syy+/1MCBAzVs2DAFBgYaHQd2zGQyafjw4XJxcVG/fv0UGxur/v37Gx0LAGBnKLYAgBfyxRdfaPDgwQoMDNSwYcOMjgMHYDKZrLv+AwYMUGxsrAYOHGh0LACAHaHYAgASbMSIEdZTj4cOHWp0HDiYwMBAmUwmDRo0SBaLRYMGDTI6EgDATlBsAQAJMnz4cA0bNkzDhw/XkCFDjI4DBzVs2DCZTCYNHjxYsbGx/F0DACQIxRYA8J8CAwP1+eefa8SIEeyiIckNHTpULi4uGjJkiGJjYznlHQDwnyi2AIBnslgsCgwM1PDhwzVy5EgNGDDA6EhwEoMHD5aLi4v1tGRepAwA8DwUWwDAU1ksFg0bNkz/+9//9OWXX/JKtUh2AwcOlMlk0sCBA63llreVAgA8DcUWAPAEi8WiIUOG6IsvvtDo0aN5b1EYZsCAAXJxcVH//v0VGxur4cOHU24BAE+g2AIA4rFYLBo8eLBGjhypr776Sr179zY6Epxcv3795OLior59+8piseh///sf5RYAEA/FFgBgZbFYNHDgQI0aNUpff/21PvvsM6MjAZKkPn36yGQyqU+fPoqNjdUXX3xBuQUAWFFsAQCSHpXa/v37a8yYMRo7dqx69uxpdCQgnt69e8vFxUWfffaZYmNj9eWXX1JuAQCSKLYAAD0qtf369dNXX32lcePGqUePHkZHAp6qV69eMplM6tWrlywWi0aNGkW5BQBQbAHA2VksFvXp00fffPONvvvuO3Xv3t3oSMBz9ezZUy4uLurRo4diY2M1ZswYyi0AODmKLQA4MYvFos8++0zjxo3T+PHj1bVrV6MjAQny6aefysXFRd27d1dsbKy+/vpryi0AODGKLQA4KYvFol69eunbb7/VhAkT1KVLF6MjAS+kW7duMplM6tatmywWi7755hvKLQA4KYotADghi8WiHj166Pvvv9fEiRPVuXNnoyMBL6Vr164ymUzq2rWrYmNjNW7cOMotADghii0AOBmLxaJPP/1U48eP1+TJk/XJJ58YHQl4JV26dJGLi4s6d+4si8Wib7/9lnILAE6GYgsATsRisahbt26aOHGipkyZoo8//tjoSECi6NSpk1xcXPTJJ58oNjZW33//PeUWAJwIxRYAnERsbKy6du2qyZMna+rUqerQoYPRkYBE1bFjR5lMJnXs2FGxsbGaMGEC5RYAnATFFgCcQGxsrLp06aIpU6Zo2rRp+uijj4yOBCSJjz/+WC4uLurQoYMsFosmTJggFxcXo2MBAJIYxRYAHFxsbKw6d+6sqVOnatq0aWrXrp3RkYAk1b59e5lMJmu5nThxIuUWABwcxRYAHFhsbKw++eQTTZs2TdOnT9eHH35odCQgWXz00UcymUxq3769YmNjNXnyZMotADgwii0AOKjY2Fh17NhR06dP18yZM9WmTRujIwHJql27dnJxcVG7du0UGxurKVOmUG4BwEFRbAHAAcXGxqpDhw6aOXOmZs2apdatWxsdCTBE27ZtZTKZ9OGHH8pisWjq1KmUWwBwQBRbAHAwDx8+VPv27TVnzhzNmTNHLVu2NDoSYKg2bdrIxcVFbdq0UWxsrKZNm0a5BQAHQ7EFAAfy8OFDffTRR5o7d67mzJmjFi1aGB0JsAmtWrWSyWRSmzZtZLFYNG3aNLm6uhodCwCQSCi2AOAgHj58qHbt2ikoKEhz585V8+bNjY4E2JSWLVvKxcVFrVq1ksVi0fTp0ym3AOAgKLYA4AAePnyotm3bav78+Zo3b56aNm1qdCTAJjVv3lwmk0ktW7ZUbGysZs6cSbkFAAdAsQUAO/fw4UO1adNGCxcu1Pz589WkSROjIwE2rVmzZnJxcVGLFi1ksVg0a9Ysyi0A2DmKLQDYsQcPHqhNmzb66aeftGDBAjVq1MjoSIBdaNKkiUwmk5o3b67Y2FjNnj1bKVLwYxEA2Cv+BQcAO/XgwQO1atVKixcv1sKFC9WwYUOjIwF2pXHjxjKZTGrWrJksFovmzJlDuQUAO8W/3gBghx48eKCWLVtq6dKl+umnn9SgQQOjIwF2qVGjRnJxcVHTpk1lsVg0d+5cyi0A2CGTxWKxGB0CAJBwMTExatGihZYvX65FixapXr16RkcC7N6yZcvUpEkT1a9fX/PmzaPcAoCdodgCgB2JiYlR8+bNtWLFCi1evFh169Y1OhLgMJYvX67GjRurXr16mjdvnlKmTGl0JABAAlFsAcBOxMTEqFmzZlq1apUWL16sOnXqGB0JcDgrV65Uo0aNVLt2bS1YsIByCwB2gmILAHYgOjpaTZs21Zo1a7R06VLVqlXL6EiAw1q1apUaNmyoWrVqaeHChZRbALADFFsAsHHR0dFq0qSJ1q1bp6VLl6pmzZpGRwIc3urVq9WgQQPVrFlTCxcuVKpUqYyOBAB4DootANiw6OhoNW7cWOvXr9eyZctUo0YNoyMBTmPNmjVq0KCBqlWrpkWLFlFuAcCGUWwBwEbdv39fjRo1UnBwsJYvX67q1asbHQlwOuvWrVO9evVUtWpVLV68mHILADaKYgsANuj+/ftq2LChNm3apBUrVqhq1apGRwKc1vr161WvXj1VqVJFixcvlpubm9GRAAD/QrEFABtz//59NWjQQJs3b9bKlSsVEBBgdCTA6W3YsEF169aVv7+/li5dSrkFABvjYnQAAMD/iYqKUv369bVlyxatWrWKUgvYiKpVq2rlypXavHmz6tevr6ioKKMjAQAew44tANiIqKgo1atXT2FhYVq1apUqV65sdCQA/7Jx40bVqVNHPj4+WrZsmdzd3Y2OBAAQxRYAbEJUVJTq1q2rbdu2afXq1fLz8zM6EoBn2Lx5s2rVqiWz2azly5dTbgHABlBsAcBg9+7dU926dbV9+3atWbNGvr6+RkcC8B+2bNmiWrVqqUKFClqxYoVSp05tdCQAcGoUWwAw0N27d1WnTh39/PPPWrt2rXx8fIyOBCCBQkJCVLNmTXl7e2vlypWUWwAwEMUWAAxy9+5d1a5dW7t27dLatWtlNpuNjgTgBYWFhalGjRoqV66cVq5cKQ8PD6MjAYBTotgCgAHu3r2rWrVqaffu3Vq3bp0qVapkdCQAL2nr1q2qXr26ypYtq1WrVlFuAcAAvN0PACSzf/75RzVr1tQvv/yi9evXU2oBO1epUiWtX79eu3fvVs2aNfXPP/8YHQkAnA47tgCQjOJK7b59+7R+/Xp5e3sbHQlAItm+fbuqVaumkiVLas2aNUqTJo3RkQDAaVBsASCZ3LlzRzVq1NCBAwe0YcMGlS9f3uhIABLZjh07VK1aNRUvXlxr166l3AJAMqHYAkAyuHPnjqpXr66DBw9qw4YNKleunNGRACSRn3/+WVWrVpWXl5fWrl2rtGnTGh0JABwexRYAktjt27dVvXp1/fbbbwoODlbZsmWNjgQgie3cuVNVq1ZV0aJFtW7dOsotACQxii0AJKHbt2+rWrVqOnz4sIKDg1WmTBmjIwFIJrt27VJAQIA++OADrVu3TunSpTM6EgA4LIotACSRW7duqVq1avr999+1ceNGlS5d2uhIAJLZ7t27FRAQoCJFimj9+vVKnz690ZEAwCFRbAEgCdy6dUtVq1bV0aNHtXHjRpUqVcroSAAMsmfPHlWpUkWFChXShg0bKLcAkAQotgCQyG7evKmqVavq2LFj2rRpk0qWLGl0JAAG27t3rypXrqyCBQtqw4YNypAhg9GRAMChUGwBIBHduHFDAQEBOnHihDZt2qQSJUoYHQmAjdi3b58qV66s/PnzKzg4mHILAImIYgsAieTGjRuqUqWKTp06pU2bNql48eJGRwJgY/bv3y9/f3/ly5dPwcHBypgxo9GRAMAhUGwBIBFERkaqSpUqOn36tDZv3iwvLy+jIwGwUQcOHJC/v788PT21ceNGyi0AJAIXowMAgL2LjIxU5cqVdebMGW3ZsoVSC+C5vLy8tGXLFp0+fVqVK1dWZGSk0ZEAwO6xYwsAr+D69euqXLmyIiIitGXLFhUtWtToSADsxMGDB+Xn56fcuXNr06ZNypQpk9GRAMBusWMLAC/p+vXr8vf31x9//KGQkBBKLYAXUrRoUYWEhCgiIkL+/v66fv260ZEAwG5RbAHgJVy7dk1+fn76888/FRISog8++MDoSADs0AcffKCQkBCdO3dOfn5+unbtmtGRAMAucSoyALygq1evyt/fXxcuXFBISIjee+89oyMBsHOHDx+Wr6+vsmfPrs2bNytLlixGRwIAu8KOLQC8gKtXr8rPz08XL15UaGgopRZAonjvvfcUGhqqCxcuyM/PT1evXjU6EgDYFYotACTQlStX5Ovrq0uXLik0NFRFihQxOhIAB1KkSBGFhobqr7/+kq+vr65cuWJ0JACwGxRbAEiAy5cvy9fXV5cvX1ZoaKgKFy5sdCQADqhw4cIKDQ3V33//LT8/P8otACQQxRYA/kNcqb1y5YpCQ0NVqFAhoyMBcGCFChVSaGhovAU1AMDz8eJRAPAcf//9t3x9fXX9+nWFhoaqQIECRkcC4CSOHz8uHx8fZc6cWSEhIXr99deNjgQANosdWwB4hkuXLsnHx0eRkZEKCwuj1AJIVgUKFFBoaKiuX78uX19f/f3330ZHAgCbRbEFgKf466+/5OPjo5s3byosLEz58+c3OhIAJ1SgQAGFhYUpMjJSPj4+unTpktGRAMAmUWwB4F/iSu3t27cVFhamfPnyGR0JgBPLnz+/wsLCdPPmTfn4+Oivv/4yOhIA2Bx+xxYAHnPx4kX5+Pjon3/+UVhYmDw9PY2OBACSpJMnT8rHx0dp06ZVaGio3nzzTaMjAYDNYMcWAP6/CxcuyGw26+7du5RaADbn3XffVVhYmP755x+ZzWZdvHjR6EgAYDMotgAg6fz58zKbzYqKiqLUArBZnp6eCgsL071792Q2m3XhwgWjIwGATeBUZABOL67UxsTEKDQ0VHny5DE6EgA815kzZ2Q2m+Xm5qbQ0FBlz57d6EgAYCh2bAE4tT///FNms1kPHjxQWFgYpRaAXciTJ4/CwsIUHR0ts9msP//80+hIAGAoii0Ap3Xu3Ll4pTZ37txGRwKABIsrtw8ePJDZbNa5c+eMjgQAhqHYAnBKf/zxh8xms2JjY7V161blypXL6EgA8MJy586tsLAwxcbGUm4BODWKLQCnExERIbPZLEkKCwtTzpw5jQ0EAK8gV65cCgsLk8Vikdls1h9//GF0JABIdhRbAE4lrtS6uLhQagE4jJw5c2rr1q2SJLPZrIiICGMDAUAyo9gCcBpnz55VpUqVlCJFCoWFhemdd94xOhIAJJp33nlHW7dulYuLi8xms86ePWt0JABINhRbAE7hzJkzqlSpklKmTKmwsDDlyJHD6EgAkOhy5MihsLAwpUiRQmazWWfOnDE6EgAkC4otAId3+vRpmc1mubu7a+vWrbzfIwCHFlduU6VKRbkF4DQotgAc2qlTp6ylNjQ0VG+//bbRkQAgyWXPnl1hYWFyd3dXpUqVdPr0aaMjAUCSotgCcFgnT56U2WyWh4eHwsLCKLUAnMrbb7+t0NBQeXh4qFKlSjp16pTRkQAgyVBsATikuFKbNm1ahYWF6a233jI6EgAku7hymzZtWpnNZp08edLoSACQJCi2ABxOeHi4KlWqpPTp0yssLExvvvmm0ZEAwDBvvfWWQkNDlS5dOpnNZp04ccLoSACQ6Ci2ABxKeHi4fHx8lDFjRoWGhuqNN94wOhIAGO7NN99UaGio0qdPL7PZrPDwcKMjAUCiotgCcBjHjx+X2WxWpkyZKLUA8C9vvPGGwsLClClTJvn4+Oj48eNGRwKAREOxBeAQjh07JrPZrCxZsig0NFSvv/660ZEAwOa8/vrrCgkJsZbbY8eOGR0JABIFxRaA3Tt69KjMZrOyZcumkJAQvfbaa0ZHAgCb9frrrys0NFRZsmSRj4+Pjh49anQkAHhlFFsAdu3IkSPy8fGx7kJQagHgv7322msKDQ3Va6+9RrkF4BAotgDs1u+//y4fHx+98cYbCgkJUbZs2YyOBAB2I1u2bNqyZYtef/11mc1m/f7770ZHAoCXRrEFYJcOHz4sHx8fvfXWW9qyZYuyZs1qdCQAsDtxv8Lx5ptvytfXl3ILwG5RbAHYnUOHDsnX11fZs2en1ALAK8qaNatCQkL09ttvy8fHR4cPHzY6EgC8MIotALvy22+/ydfXVzly5NCWLVuUJUsWoyMBgN3LkiWLNm/erBw5csjHx0e//fab0ZEA4IVQbAHYjYMHD8rX11c5c+bU5s2blTlzZqMjAYDDiCu377zzjvz8/Ci3AOwKxRaAXfj111/l5+en3LlzU2oBIIlkzpxZmzdvVq5cueTr66uDBw8aHQkAEoRiC8DmHThwQH5+fsqTJ482b96sTJkyGR0JABxW5syZtWnTJuXJk0e+vr46cOCA0ZEA4D9RbAHYtP3798vPz0+enp7atGmTMmbMaHQkAHB4mTJl0qZNm+Tp6Sl/f3/KLQCbR7EFYLP27dsnf39/5c+fn1ILAMksY8aM2rhxo9599135+flp//79RkcCgGei2AKwSXv37pW/v78KFCig4OBgZciQwehIAOB04spt/vz55e/vr7179xodCQCeimILwObs2bNH/v7+KlSoEKUWAAyWIUMGBQcHq0CBAqpcubL27NljdCQAeALFFoBN+eWXX1S5cmUVKVJEGzZsUPr06Y2OBABOL67cFipUSJUrV9Yvv/xidCQAiIdiC8Bm7Nq1S5UrV9Z7771HqQUAG5M+fXoFBwerSJEiqlKlinbv3m10JACwotgCsAk7d+5UQECAPvjgA61fv17p0qUzOhIA4F/SpUunDRs26L333lOVKlW0a9cuoyMBgCSKLQAb8PPPPysgIEBFixal1AKAjUuXLp3Wr1+vDz74QAEBAdq5c6fRkQCAYgvAWDt27FDVqlXl5eWldevWKW3atEZHAgD8h7hyW7RoUQUEBOjnn382OhIAJ0exBWCY7du3q2rVqipRogSlFgDsTNq0abVu3ToVL15cAQEB2rFjh9GRADgxii0AQ2zbtk3VqlVTqVKltGbNGqVJk8boSACAF5Q2bVqtXbtWJUuWVNWqVbV9+3ajIwFwUhRbAMlu69atqlatmkqXLk2pBQA7lyZNGq1Zs0alSpVStWrVtHXrVqMjAXBCFFsAySosLEzVq1dX2bJltXr1anl4eBgdCQDwiuLKbenSpVW9enWFhYUZHQmAk6HYAkg2ISEhql69usqVK0epBQAH4+HhodWrV6tcuXKqUaOGQkNDjY4EwIlQbAEkiy1btqhmzZry9vbWqlWrlDp1aqMjAQASmYeHh1atWqXy5curRo0aCgkJMToSACdBsQWQ5DZv3qyaNWuqYsWKWrlyJaUWABxY6tSptXLlSlWoUEE1atTQli1bjI4EwAlQbAEkqU2bNqlWrVoym81asWIFpRYAnEBcua1UqZJq1qypzZs3Gx0JgIOj2AJIMsHBwapVq5Z8fHy0fPlyubu7Gx0JAJBM3N3dtWLFCpnNZtWqVUsbN240OhIAB0axBZAkNmzYoDp16sjf359SCwBOyt3dXcuXL5evr69q166t4OBgoyMBcFAUWwCJbv369apbt64qV66spUuXys3NzehIAACDuLu7a9myZfL391edOnW0YcMGoyMBcEAUWwCJat26dapbt66qVKmiJUuWUGoBAHJzc9PSpUtVuXJl1alTR+vWrTM6EgAHQ7EFkGjWrFmjevXqqVq1apRaAEA8bm5uWrJkiapWrap69epp7dq1RkcC4EAotgASxerVq1W/fn1Vr15dixYtUqpUqYyOBACwMW5ublq8eLGqVaum+vXra82aNUZHAuAgKLYAXtmqVavUoEED1axZUz/99BOlFgDwTKlSpdKiRYtUvXp11a9fX6tXrzY6EgAHQLEF8MKioqK0b98+SdLKlSvVsGFD1a5dm1ILAEiQuHJbq1YtNWjQQCtXrpQk7du3T1FRUQanA2CPKLYAXtiXX36pBg0aaPny5WrYsKHq1KmjBQsWKGXKlEZHAwDYiZQpU2rhwoWqXbu2GjVqpBUrVqhBgwb68ssvjY4GwA6ZLBaLxegQAOyHxWJRgQIF9Pbbb2v79u2qV6+e5s2bR6kFALyUmJgYNW/eXCtWrFCFChV08eJFHTt2TCaTyehoAOwIO7YAXsihQ4d04sQJhYWFycvLS5K0bds2g1MBAOxV3Azx8vLS1q1bFR4ersOHDxucCoC9odgCeCFffPGF9eM9e/bo4sWLypw5s4GJAAD2LHPmzPrrr7+0Z88exZ1IOGLECINTAbA3FFsAL+TevXt66623NHbsWJ0/f147duxQsWLFjI4FALBTxYoV044dO3T+/HmNHTtWb731lu7du2d0LAB2ht+xBQAAAADYNXZsAQAAAAB2LYXRAYCkdO7cOV29etXoGEhEWbNm1TvvvGN0DABweMxQx8MMhSOj2MJhnTt3TgULFtTdu3eNjoJE5OHhoWPHjjGYASAJMUMdEzMUjoxiC4d19epV3b17V0FBQSpYsKDRcZAIjh07ppYtW+rq1asMZQBIQsxQx8MMhaOj2MLhFSxY0Pp+qwAAIOGYoQDsBS8eBbyEiIgI+fv7P/P6WbNm6datW8+9j7CwMB06dCixo8UzcOBA5cyZ86lZr127pkyZMikoKOiZx4eEhMhkMun8+fOSpPv376t169aqUKGC6tatq5s3b0qSAgMDVbBgQZnNZpnNZkVHRyfNJwQAQDKYOnWqdaYVKFBADRo0eOZtW7duHW/ONmjQQJUqVVKJEiU0btw46+WpU6e23ufUqVOTND/gjCi2QBJIimJ7586dF87RtWtXhYaGPvW6ESNGyNvb+5nHxsbG6uuvv1aJEiWsl82ePVu5cuXS9u3bVb16dY0dO9Z63aBBgxQWFqawsDClSpXqhbMCAPC4hw8fJsr9xMbGvvDvCn/88cfWmVaxYkU1adLkqbc7cODAE/N+wYIF2rp1q3bv3q1Jkybp9u3bkqS3337bep8ff/zxy30yAJ6JYgu8ohkzZqhkyZLy9fVVv379FBISooMHD6pRo0Zq3769IiMj5e/vL7PZrHLlyun48eO6fv26Zs2apS+++EJms/mZpfXOnTsKCgpSrVq11Lt37xfO9tZbb8nF5cmn+alTp3Tt2jUVL178mccGBQWpdu3aSpMmjfWy0NBQ1atXT5JUt27deKV5zJgx8vb2jrc6DQDAi4iIiFDJkiXVunVrtWzZUrNmzVL9+vXVsGFDFSxYUIsWLVLDhg1VtGhRff/998+9r0OHDqlv377y9vbWkSNHXipPVFSUNm7cqNq1az/1+uHDh2vQoEHxLotb3L17967eeecdeXh4SJIuXbqkSpUqqW7dujpz5sxL5QHwbPyOLfCKZs2apcWLFytXrlyKjY2Vi4uLihYtqqCgIGXPnl0xMTFat26dUqVKpfXr12v06NGaOXOm2rZtK09PT7Vs2fKJ+9y4caPmzJmjq1evqnbt2poxY4ayZcsmSdqzZ4/69u37xDFdu3ZVw4YNE5R56NCh+t///qe5c+c+9fp79+5pzpw52rBhgxYuXGi9PO70ZUnKlCmTrl27Jknq1q2bhg0bpvv376tOnToqWrSofHx8EpQFAIDHRUREaPPmzcqQIYNmzZql2NhYLVu2TDt27FCTJk108uRJubi4qEiRIurevXu8Y69cuaIZM2YoODhY+fPnV/PmzTV69GiZTCZJUufOnXX06NF4x6RNm1Zr1qx5apbVq1fL399f7u7uT1y3Zs0aeXl5Wefz4+rUqaNdu3apU6dOcnV1tX5eWbNm1ZYtW9SuXTuFhYW9zJcHwDNQbIFXNG7cOP3vf//TvXv31LRp0ydWdW/cuKEuXbro0qVLio6OVrp06f7zPufNm6fTp0+rW7duql27ttKmTWu9rlSpUq80DHfu3KksWbIob968z7zNt99+q08++UQpUsT/JyJLliyKjIxUrly5dOPGDWXJksV6uSS5u7urQYMG2rdvH8UWAPBSihQpogwZMlj/HHd2Ufbs2VWgQAHrDujThIeHa8aMGapVq5Zat26t999/P971kyZNeqEsc+bMeeoZUw8fPtTYsWO1evVqXbly5YnrV65cqX/++cd6GnOhQoWUNWtWSZKfn586duz4QjkA/DeKLfCKChYsqOnTpysqKkrvvvuuateurVSpUunBgweSHp3SW6xYMQ0YMEDr1q2z/l7q47f5t9mzZ+vatWv66aefVK9ePWXNmlVt27ZVQEDAK+/Y7tu3T4cOHVLVqlV16tQppUmTRnnz5lXZsmWttzly5Ii2bt2qadOm6dChQ2rVqpXWrFkjs9msVatWqVixYlq1apXMZrOkR+U9Y8aMslgsCg0NVbNmzV70ywgAgCRZdzjjxO22/vvjp/H29tbx48f1888/a/LkyTp69KiqVKmijh07KmvWrC+0Y3vlyhUdO3ZMFStWfOK6S5cuKTIyUg0aNNC9e/d05MgRDR8+XIMHD9bDhw+VMmVKpU6d2vrfnTt3lDp1arm6uur3339X5syZX+RLAiABKLbAK+rcubPOnj2r6OhoffLJJ5Kk+vXrq127dipevLjatm2r5s2ba/v27SpUqJD1uMqVK6tHjx5as2aN5syZ88QKdJYsWdS5c2fr/e/YsUPSi+3Yfvfdd1q8eLGOHTsmf39/TZo0Sd27d7eeuhUYGChPT0+VLVtWly5d0ldffaVvvvkm3islm81mzZ07V2nSpFHbtm3Vvn17VaxYUZkyZdLs2bMlST169FB4eLgsFosqVKjwzN9FAgAgqZlMJnl7e8vb21sxMTFav369/v77b2XNmvWFdmwXLlyoxo0bxyvTs2bN0ttvv63KlSvr119/lfToFOP27dtr6NChun37tmrVqiXp0TsJNG3aVLlz59aePXvUsWNH61lbU6ZMScTPGIAkmSwWi8XoEEBSOHDggIoXL679+/fzHnwOgu8pACQP/r11PHxP4eh4VWQAAAAAgF2j2AIAAAAA7BrFFgAAAABg1yi2gEECAwPjvUiTLduwYYPKly8vs9ksX19f/fnnn5IefQ4FCxaU2WyW2WxWdHT0E8du2bJFZcuWVdmyZbVgwQLr5f7+/sqWLZtGjBhhvezEiRPy8vJS2rRprS+WBQDAv9nTDI2MjFSVKlVUqVIllStXzvqiUwmZoeXKlVOlSpVUsmRJ6wyNjo5W48aNVaFCBZUqVUqbNm2SJJ05c0YVK1a03t8ff/yRfJ8kYAMotkAie/jwYbI/jsViUUJeB+5ls/n6+urnn39WWFiYWrZsqe+//9563aBBgxQWFqawsDClSpXqicfr1auX1qxZo5CQEI0ePVq3b9+W9OiVJb/66qt4t8+ePbu2bNmSoLctAgA4HkecofPmzVP58uW1detWjRkzJt6C7vNmqCSFhYVp69at2rJliwYOHChJ2rhxo9KkSaPt27dr6dKl6t+/v6RH79H70UcfKSwsTO3bt483qwFnQLGFU4mIiFD58uXl4+Mjs9msyMhI/f333/Lz81OVKlXUuXNn+fv7S5Latm1r3TWMGxLSo7fQ8fX1VYkSJTR48GDrfefMmVNdunRRlSpVdPPmTTVu3Fi+vr7y8fHRiRMnJEnLly9X0aJFVbt2be3fv/+ZOWNiYtShQwf5+vrK29tbu3btsmbq1KmTatWqpeDgYHl6emrQoEHy8/PT+fPn1bRpU1WqVEnly5e33v+/j3kZjw/bGzduxHvD+zFjxsjb21vjxo174rhTp04pV65cypIli1KnTq1y5cpp7969kh6V2H/z8PBQpkyZXiojACBpMUNfboYWLFhQt27dkiRdv35dr732mvW6581Q6f/m7+3bt1W4cGFJUt68eXX//n1ZLBZFRkZa769w4cK6cePGUx8HcAa8jy2cSkhIiCpXrqzAwEBJj1Zpe/bsqXbt2qlFixaaMWOGdYA+S/v27fXpp5/KYrGoXLly6tChg3LmzKmLFy+qT58+ypUrl/r376/69euradOmOnLkiPr27atly5apf//+2rNnj9KlSydfX99nPsb06dOVN29e/fjjj7py5Ypq165tHczZs2fX5MmTJT16D93q1avriy++0HfffacCBQpo4cKFCg8PV5s2bbR79+4njnnci7xR/fLly/XFF1/o5s2bWr9+vSSpW7duGjZsmO7fv686deqoaNGi8vHxsR5z7dq1eEU1U6ZMunbt2nO/vgAA28QMjS+hM9TLy0tDhgxRkSJFdOPGDW3btk3Sf89QSbp3754CAgJ05MgRjRo1SpKUJ08e3b17VwUKFNCNGze0cuVKSZKfn58CAgI0ffp0RUVFac+ePc/9XgCOhmILp9K4cWONHDlSLVq0UM6cORUYGKjw8HB169ZN0qPfZZk/f74kxXtD9sdPUVq6dKmmTZsmk8mks2fP6vz588qZM6eyZ8+uXLlySZIOHz6srVu36ocffrDe15UrV/Taa68pQ4YMkqQyZco8M+fhw4e1c+dObdiwQZKsK7CS5O3tbf3Y1dVV5cqVkyQdP35cDRo0kCTlz58/XoF8/JjHvcgb1derV0/16tXTwoULNXDgQC1atEhZsmSRJLm7u6tBgwbat29fvKGcJUsWRUZGWv9848YN6zEAAPvCDI0voTN0zJgxql+/vnr37q3du3erS5cuWr9+/X/OUElKnTq1tm3bpqtXr6pkyZJq3LixFi5cqOzZs2vFihWKiIhQvXr19Ouvv6pfv3763//+p4YNG2rhwoUaMGDAUws54KgotnAqLi4uGjlypCSpXbt2Cg4OVr58+fTLL78ob9681tVZScqcObPOnTsnSdbTZyVpyJAhOn78uNzc3FS+fHnrwHZ1dbXepnDhwipbtqzq1asn6dELPbi6uurvv//WrVu3lC5dOu3Zs0dFihR5as7ChQvL09NTPXv2tB4f5/HHMZlM1h8eChQooO3bt8vf31/h4eHxCuTjxzwuoavNUVFRcnd3l/Ro19XDw0PSox8WMmbMKIvFotDQUDVr1izecZ6enoqIiFBkZKQ8PDy0c+dOffnll0/NAgCwbczQ+F7krKds2bJZ/x9XtP9rhkZHRytFihRycXFRmjRp5O7ubp3FcfeXKVMm3blz57mPAzgLii2cypo1azR+/Hi5urrKzc1N3t7eKlGihJo3b66ZM2fGG5Lt27dX8+bNNX/+fOXOndt6ef369VW+fHkVKFBAadOmferjDBo0SJ988onGjx8vSQoICFC/fv305ZdfqmLFisqRI4cyZ878zJwdOnRQ165drSu3xYoV09ixY5/7uXXo0EFt27ZVxYoV9eDBA+tjP09CV5t//PFHLV26VCaTSW5ubpoyZYokqUePHgoPD5fFYlGFChVUu3Zt6+WDBg1StmzZ9PXXX6t69eqSpN69eyt9+vSSHv1Q9Msvv+j+/fv65ZdftHr1akVGRqpRo0Y6evSojhw5ooCAgHgvsgEAMA4zNL6EztBu3bqpVatWmjlzpu7du6fRo0dL+u8ZevPmTbVr106urq66f/++hg0bJjc3N7Vs2VLNmjVTpUqVdPfuXX3xxReSpMGDB6tjx45KkSKFYmJirLMacBYmS0JeBg6wQwcOHFDx4sW1f/9+eXl5JeiYiIgItW/fXps3b07idHgZL/M9BQC8OGao42GGwtGxYwsYrHXr1tbTtaRHp28tW7bMwEQAANgHZiiAOBRb4DG5cuVK9pXmOXPmJOvjAQCQFJihAIzE+9gCdsDT0zNZHmfKlCkqVaqUKlasqGbNmun+/fuSpH379qlMmTKqVKmSqlWrpps3b8Y7rmLFitb3KAQAwFYl1zwdPny4zGazzGazcuXKpc8++0yS9Oeff8rf318VKlRQ7969kyUL4CwotgCs/Pz8tHv3bm3btk05cuRQUFCQJGnUqFEaPXq0tm7dqvLly8dbIV++fLkyZsxoUGIAAGzP0KFDFRYWprCwMOXLl09NmjSRJPXr108DBw7U9u3bdfHiRYWGhhqcFHAcFFvgFURERKh8+fLy8fGR2WxWZGSktm3bJh8fH+srHN67d0+SZDab1bNnTwUEBMhsNmv+/PkKCAhQ0aJFrW9obzab1aVLF1WuXFl+fn66fPlyvMeLiYlRhw4d5OvrK29vb+sbzo8YMUKlSpWSr6/vf77y4/N4enrKxeXRPwtubm7WtzgoXLiw9W0DIiMj9dprr0mSHjx4oMmTJ6tLly4v/ZgAADjaPI1z8eJFnT9/XqVKlZL06AWcfH19JUl169al2AKJiGILvIKQkBBVrlxZoaGhCgsLU8aMGVW8eHGFhoZq+/btKliwoBYtWmS9faVKlRQcHCxPT0/t3btXwcHB6t27t2bMmGG9TenSpbVp0ya1aNFCX331VbzHmz59uvLmzauQkBAtX75cvXr1kiTNmzdPoaGhCgkJUY8ePZ7IWb9+fespUXH/Pe/U4WPHjmn9+vVq1KiRJKlevXrq1q2bihQpop07d6p+/fqSpB9++EEtW7aUm5vbS38NAQBw1Hk6b948NW/e3Prn2NhY68eZMmXStWvXXvhrBeDpePEo4BU0btxYI0eOVIsWLZQzZ04FBgbqyJEjGjx4sO7fv6+///7b+r6tklS8eHFJUvbs2ZU3b17rx1u3brXeply5ctb/L1++PN7jHT58WDt37tSGDRskybqLOmHCBHXp0kUPHjzQJ598Im9v73jHvcgrREZERKhNmzZatGiR0qRJI0nq1KmTli1bphIlSmjUqFEaO3asOnXqpBUrVmjjxo3atm1bgu8fAIB/c8R5KklBQUFauXKl9c9xZ0XFPWaWLFle6P4APBvFFngFLi4uGjlypCSpXbt2Cg4O1rRp0/T555+rbNmy6tu3rx5/q2iTyfTUjx+/ze7du+Xp6andu3crf/788R6vcOHC8vT0VM+ePSVJ0dHRkqSyZcvKz89P586dU7169bR///54x9WvX1/Xr1+Pd5mnp6emTZsW77JLly6pUaNGmj59uvLkyRPvumzZsln/f+rUKR07dky3bt1S9erVdf36df3111+aMmWKOnbsmICvHAAA/8fR5qkkHTx4UBkyZFCuXLmslxUrVkxbt25VpUqVtGrVKn344YcJ+voA+G8UW+AVrFmzRuPHj5erq6vc3Nzk7e2tO3fu6KOPPlKBAgWUPn36eCvMCXHgwAHNnj1bDx8+1IIFC+Jd16FDB3Xt2lU+Pj6SHg3IsWPHql69eoqKilJUVNRTf981oSvM/fv3199//63u3btLkpo3b66PP/5Yo0aNUpMmTeTu7i4XFxcFBQXprbfe0p49eyRJYWFhCgoKotQCAF6Ko81TSZo7d65atmwZ77JRo0apXbt2io6OVokSJayPD+DVmSyPL20BDuTAgQMqXry49u/fLy8vL6PjJIjZbFZQUJCyZ89udBSbZI/fUwCwR/b+7y3z9En2/j0F/gsvHgUAAAAAsGucigzYkLCwMKMjAABg95ingPNhxxYAAAAAYNcotkAyiIiIkL+/f7I93pIlS1SwYEG5u7vHu3zVqlUqXbq0KlSooIULFz712JCQEPn7+8vHx0cDBgyQJJ04cUJeXl5KmzatduzY8cQxQ4cOlaenZ+J/IgAAp5fcM/SLL75QxYoVVb58ebVu3VoxMTGSHv3ebtmyZWU2m9W5c+dnHh8eHq6UKVNa52VYWJjefPNN6/vexr3w4rNmNYCXw6nIgAMym8369ddfVaRIEetlsbGx6tOnj/bt2yd3d3eVL19eNWrUULp06ay3uXbtmr755hutXbtWbm5u1suzZ8+uLVu2WN8W4XEXLlzQyZMnk/YTAgAgmfTp00eDBg2SJLVu3VobN25UjRo1JEmLFy/+zxekCgwMlNlsjndZjRo1nnhLoKfNagAvjx1b4CX17t1bS5culSQ9ePBA77//vmJiYjRw4ED5+vrKy8tLkydPfuK4tm3bxlvFbd++vSTp999/l7+/v3x9fdWoUSPdvXv3pbNlzZr1iRXgq1evKlu2bEqXLp1SpkypPHnyaO/evfFus3btWmXLlk1169aVv7+/du/eLUny8PBQpkyZnvpYgYGBGjx48EtnBQA4H1ueoalSpZL0aEH4wYMH1jOSTCaTmjZtKh8fH23evPmpx27btk25cuXS22+/He/yjRs3ytvbW507d7Zme9qsBvDyKLbAS2rbtq1mz54tSQoODpavr69SpkypQYMGKSQkRLt27dK4ceOspzD9l86dO2vGjBkKCQmR2WzW1KlT410fHR1tPY3p8f8SWiqzZs2qK1eu6MKFC7p586Z27dr1xJvMX7hwQceOHdPy5cs1ffp0tWvX7rn3eejQIUmP3ugeAICEsvUZOmzYMOXLl083btxQjhw5JD3ard2xY4eCgoLUtWtX3bx5M94xFotFI0eOVL9+/eJdXrx4cZ04cUI7duxQ1qxZNXr06AR9TgBeDKciAy+pSJEiunLlii5fvqzZs2dbfx918uTJWrFihVxdXXX58mVdvnw53nEmk8n68eNvI33kyBG1bt1aknT//v0nTmNKlSrVK73Ko4uLi6ZMmaKWLVsqXbp0Klq0qN566614t8mcObN8fHzk7u6unDlzKn369Lp+/boyZ8781PscOnSoJkyY8NKZAADOydZn6Oeff67AwEB16dJFs2bNUufOnZU1a1ZJ0ttvvy0vLy+dOHFCJUuWtB6zcOFC+fv7K2PGjPHu6/Ff+WnZsuVTf60HwKuj2AKvoEWLFpo4caIiIiJUrFgxRUZGaubMmTp06JBiYmKUP3/+eINXelQez507J0nxTgUuUqSIFixYoDfffFPSo9Xlx0VHR6tKlSpPZPD29taIESMSlDduhfr27dtq0KBBvIEsST4+Plq6dKksFotu3rypyMjIZ56CLEmnT5+2ngb2119/qUuXLpo4cWKCsgAAnJutztCoqCi5u7vLZDIpQ4YM8vDwkMVi0e3bt5U+fXrduXNHv/32m3LlyhXvuIMHD2rfvn3avHmzDh8+rOPHj2v+/PnKkiWLMmTIIOnRCzTmz5//5b5gAJ6LYgu8gubNmytHjhwaPny4JCljxowqVKiQvL29VahQIWXJkuWJY9q3b6/mzZtr/vz5yp07t/XyiRMnqm3bttbTrvr27auqVatar3+R1eawsDCNGDFCFy9elL+/vzp27KhGjRqpb9++2rt3r1KkSKFRo0YpZcqUkh79cDFv3jzly5dP1apVU6VKlXT//n2NHTtWJpNJkZGRatSokY4ePaojR44oICBAI0aM0OHDh62P6enpSakFACSYrc7Qzp0768yZM3r48KHy5cun4cOH68GDB/Lx8VHq1KkVHR2twYMHK1u2bJL+b4Y+fopx27Zt1b59e+XJk0eTJk3SzJkzlTp1amXOnFkzZsyQ9OxZDeDlmCz/XgoDHMSBAwdUvHhx7d+/X15eXkbHQSLgewoAyYN/bx0P31M4Ol48CgAAAABg1yi2AAAAAAC7RrEFAAAAANg1XjwKDu/YsWNGR0Ai4XsJAMmLf3cdB99LODqKLRxW1qxZ5eHhoZYtWxodBYnIw8PD+l6CAICkwQx1TMxQODJeFRkO7dy5c7p69arRMRLswYMHatiwoXLlyqVvv/02yR6nR48e+uOPP7R48WKlSGFf61tZs2bVO++8Y3QMAHB4zNCnY4YCtoliC9iQOXPmqE2bNtq3b5+KFy+eZI+zb98+lSxZUnPmzFGrVq2S7HEAAEguzFDAuVFsARvx4MEDFSxYUIUKFdLKlSuT/PFq166t48eP6+jRo3a34gwAwOOYoQB4VWTARsybN0+nTp1SYGBgsjxeYGCgTp48qfnz5yfL4wEAkFSYoQDYsQVswIMHD1SgQAG99957Wr58ebI9bt26dXXkyBEdO3aMFWcAgF1ihgKQ2LEFbMLcuXN1+vTpZFtpjhMYGKhTp04pKCgoWR8XAIDEwgwFILFjCxguJiZG+fPnV7FixbR06dJkf/z69evrt99+0/Hjx5UyZcpkf3wAAF4WMxRAHHZsAYPNmTNHZ8+e1bBhwwx5/GHDhunMmTOaO3euIY8PAMDLYoYCiMOOLWCgmJgY5cuXT8WLF9eSJUsMy9GgQQP9+uuvCg8PZ8UZAGAXmKEAHseOLWCg2bNnKyIiwrCV5jjDhg3T2bNnNWfOHENzAACQUMxQAI9jxxYwSHR0tPLly6dSpUpp0aJFRsdRo0aNtG/fPoWHhytVqlRGxwEA4JmYoQD+jR1bwCCzZs3SuXPnDF9pjjNs2DD98ccfmj17ttFRAAB4LmYogH9jxxYwQHR0tN59912VLVtWCxcuNDqOVZMmTbR7926dPHmSFWcAgE1ihgJ4GnZsAQPMmDFDf/75p4YOHWp0lHiGDh2qP//8U7NmzTI6CgAATzVz5kxmKIAnsGMLJLP79+/r3XffVfny5bVgwQKj4zyhadOm2rVrFyvOAACbwwwF8Czs2ALJbMaMGTp//rzNrTTHiVtxnjFjhtFRAACIhxkK4FnYsQWS0f379+Xp6amKFStq3rx5Rsd5pubNm2v79u06deqU3NzcjI4DAAAzFMBzsWMLJKNp06bp4sWLNrvSHGfo0KG6ePGipk+fbnQUAAAkMUMBPB87tkAyiYqKUt68eeXr66u5c+caHec/tWzZUmFhYTp16pTc3d2NjgMAcGLMUAD/hR1bIJn8+OOPunTpkoYMGWJ0lAQZMmSI/vrrL1acAQCGmzZtGjMUwHOxYwskg6ioKOXJk0f+/v6aM2eO0XESrFWrVgoJCdHp06dZcQYAGCJut9bPz48ZCuCZ2LEFksHUqVN1+fJlu1lpjjNkyBBdunRJP/74o9FRAABOaurUqfr777+ZoQCeix1bIIndu3dPefLkUUBAgF2+aXubNm20adMmnT59WqlTpzY6DgDAiTBDASQUO7ZAEpsyZYquXLlidyvNcYYMGaLLly9r6tSpRkcBADgZZiiAhGLHFkhCd+/eVZ48eVS9enW7frP2Dz/8UBs2bNCZM2dYcQYAJAtmKIAXwY4tkIR++OEHXb16VYMGDTI6yisZPHiwrly5oilTphgdBQDgJKZMmaKrV69q8ODBRkd5JcxQIHmwYwskkbt37yp37tyqWbOmQ7zcf7t27bRu3TqdOXNGHh4eRscBADiwuN3aGjVqMEMBJAg7tkASmTx5sq5fv273K81xBg8erGvXrumHH34wOgoAwMFNnjxZ165dY4YCSDB2bIEk8M8//yh37tyqU6eOQ73Mf/v27bV69WqdOXNGadKkMToOAMABMUMBvAx2bIEkMGnSJEVGRtr979b+2+DBg3X9+nVNnjzZ6CgAAAfFDAXwMtixBRLZnTt3lDt3btWvX98hXyji448/1ooVK3T27FlWnAEAiYoZCuBlsWMLJLKJEyfq5s2bGjhwoNFRksSgQYMUGRmpSZMmGR0FAOBgJk2axAwF8FLYsQUS0Z07d5QrVy41bNjQoV8gomPHjlq2bJnOnj2rtGnTGh0HAOAA4nZrGzRowAwF8MLYsQUS0YQJE3Tr1i2HXWmOM2jQIN28eVMTJ040OgoAwEFMmDDBoXdr4zBDgaTBji2QSG7fvq1cuXKpSZMmTnGKUadOnbR48WKdPXtW6dKlMzoOAMCOMUMBvCp2bIFEMn78eN25c8fhV5rjDBw4ULdv39aECROMjgIAsHPMUACvih1bIBHcunVLuXLlUvPmzZ1qSHXp0kULFy5UREQEK84AgJdy69Yt5c6dW82aNWOGAnhp7NgCiWD8+PH6559/1L9/f6OjJKsBAwbozp07Gj9+vNFRAAB2Km63dsCAAUZHSVbMUCBxsWMLvKKbN28qd+7catGihVMOp65du2r+/PmKiIhQ+vTpjY4DALAjzFBmKJBY2LEFXtH333+vu3fvOt1Kc5wBAwbo7t27+v77742OAgCwM8xQZiiQWNixBV7BjRs3lDt3brVu3Vrfffed0XEM0717d82dO1cRERHKkCGD0XEAAHaAGfoIMxRIHOzYAq/gu+++U1RUlNP9bu2/9e/fX1FRUU79gwkA4MUwQx9hhgKJgx1b4CXduHFDuXLl0ocffqhx48YZHcdwPXr00OzZs3X27FllzJjR6DgAABvGDI2PGQq8OnZsgZf07bff6v79++rbt6/RUWxCv379WHEGACRI3Azt16+f0VFsAjMUeHUUW+AlREZGaty4cerUqZPefPNNo+PYhDfffFOffPKJxo0bpxs3bhgdBwBgox6foW+88YbRcWwCMxR4dRRb4CWMGzdOMTExrDT/S79+/RQdHc1pZQCAZ2KGPh0zFHg1FFvgBV2/fl3ffvutOnfurNdff93oODbljTfeUKdOnfTtt98qMjLS6DgAABvDDH02Zijwaii2wAsaO3asHj58yO/WPkPfvn0VExOjsWPHGh0FAGBjmKHPxwwFXh7FFngB165d03fffacuXbrotddeMzqOTXr99dfVpUsXfffdd7p+/brRcQAANuLatWv6/vvvmaHPwQwFXh7FFngBY8eOVWxsrHr37m10FJvWp08fPXz4kBVnAIBV3G5tnz59jI5i05ihwMuh2AIJdPXqVX3//ffq2rUrK83/4bXXXrOuOF+7ds3oOAAAgz0+Q7Nly2Z0HJvGDAVeDsUWSKBvvvlGFouFleYE6tOnjywWi7755hujowAADMYMfTHMUODFUWyBBLhy5YrGjx+vbt26KWvWrEbHsQvZsmVT165dNX78eF29etXoOAAAgzBDXxwzFHhxFFsgAb7++muZTCZ+t/YFxX29vv76a4OTAACMwgx9OcxQ4MVQbIH/cPnyZU2YMEHdu3dXlixZjI5jV7Jmzapu3bppwoQJunLlitFxAADJ7MqVK8zQl8QMBV4MxRb4D19//bVcXV3Vq1cvo6PYpc8++0wmk4kVZwBwQl999RUz9BUwQ4GEo9gCz3H58mVNnDiRleZXkCVLFnXv3l0TJkzQ5cuXjY4DAEgmzNBXxwwFEo5iCzzHmDFjlCJFClaaX9Fnn30mV1dXffXVV0ZHAQAkE2Zo4mCGAglDsQWe4dKlS5o0aZI+/fRTZc6c2eg4di1z5sz69NNPNXHiRP39999GxwEAJDFmaOJhhgIJQ7EFnmHMmDFKlSqVevbsaXQUh9CrVy+lTJmSFWcAcAJfffUVMzQRMUOB/0axBZ7ir7/+0uTJk9WjRw9lypTJ6DgOIVOmTOrRo4cmTZqkS5cuGR0HAJBELl26xAxNZMxQ4L9RbIGnGDNmjNzc3NSjRw+joziUnj17KlWqVBozZozRUQAASWT06NFKlSoVMzSRMUOB56PYAv/y119/6YcfflDPnj2VMWNGo+M4lIwZM6pHjx6aPHmy/vrrL6PjAAASGTM06TBDgeej2AL/MmrUKLm7u7PSnER69OghNzc3jR492ugoAIBExgxNWsxQ4NkotsBjLly4oClTpqhXr17KkCGD0XEcUsaMGdWrVy/98MMPunjxotFxAACJhBma9JihwLNRbIHHjBo1Sh4eHvr000+NjuLQPv30U6VOnZoVZwBwIKNHj2aGJgNmKPB0FFvg/7tw4YKmTp2qzz77TOnTpzc6jkPLkCGDPvvsM02ZMkUXLlwwOg4A4BUxQ5MPMxR4Ooot8P99+eWXSps2rbp162Z0FKfQvXt3eXh4aNSoUUZHAQC8oi+//FJp0qRhhiYTZijwJIotIOnPP//Ujz/+yEpzMkqfPr0+++wzTZ06VefPnzc6DgDgJTFDkx8zFHiSyWKxWIwOARitc+fOWrRokc6ePat06dIZHcdp3Lp1S7lz51bTpk01ceJEo+MAAF4CM9QYzFAgPnZs4fTOnTunadOmqXfv3gzkZJY+fXr17t1b06ZN059//ml0HADAC2KGGocZCsTHji2c3ieffKKlS5fq7NmzSps2rdFxnM7t27eVO3duNW7cWJMmTTI6DgDgBXTq1ElLlixhhhqEGQr8H3Zs4dT++OMPzZgxQ3369GEgGyRdunTq06ePpk2bpnPnzhkdBwCQQH/88YemT5/ODDUQMxT4P+zYwql17NhRy5YtY6XZYHfu3FHu3LnVoEED/fDDD0bHAQAkQNwMjYiIUJo0aYyO47SYocAj7NjCaUVERGjGjBnq27cvpdZgadOmVZ8+fTRjxgz98ccfRscBAPyHx2copdZYzFDgEXZs4bQ6dOigVatW6cyZMwxlG/DPP/8od+7cqlu3rqZOnWp0HADAczBDbQszFGDHFk7q7NmzmjVrFivNNiRNmjTq27evZs6cqYiICKPjAACegRlqe5ihADu2cFIfffSR1q5dqzNnzsjDw8PoOPj//vnnH+XJk0e1a9fWjz/+aHQcAMBTtG/fXmvWrGGG2hhmKJwdO7ZwOmfOnNHs2bPVr18/BrKNSZMmjfr166dZs2bpzJkzRscBAPwLM9R2MUPh7NixhdNp166d1q1bx0qzjbp7967y5MmjGjVqaPr06UbHAQA8pl27dlq/fr3OnDmj1KlTGx0H/8IMhTNjxxZO5dSpU5ozZ4769+9PqbVRHh4e6tevn2bPnq3Tp08bHQcA8P/FzdB+/fpRam0UMxTOjB1bOJW2bdtq48aNOn36NEPZht27d0958uRR1apVNXPmTKPjAADEDLUXzFA4K3Zs4TROnjypuXPnqn///gxkG5c6dWr1799fc+fO1alTp4yOAwBO79SpUwoKCmKG2gFmKJwVO7ZwGq1bt9aWLVt0+vRpubu7Gx0H/+HevXvKmzevqlSpolmzZhkdBwCcWps2bbR582ZmqJ1ghsIZsWMLp3DixAnNmzdPAwYMYCDbidSpU2vAgAGaO3euTp48aXQcAHBaJ06cUFBQEDPUjjBD4YzYsYVTaNWqlUJDQ3Xq1CmGsh2JiopS3rx55efnpzlz5hgdBwCcEjPUPjFD4WzYsYXDCw8P1/z581lptkPu7u4aMGCA5s2bp/DwcKPjAIDTYYbaL2YonA07tnB4LVq00LZt23Tq1Cm5ubkZHQcvKCoqSp6enjKbzQoKCjI6DgA4FWaofWOGwpmwYwuHduzYMS1YsEADBw5kINspd3d3DRw4UAsWLNDx48eNjgMATuP48ePMUDvHDIUzYccWDq1Zs2b6+eefdfLkSYayHbt//77effddVahQQfPmzTM6DgA4hebNm2vHjh3MUDvHDIWzYMcWDuvo0aP66aefNGjQIAaynXNzc7OuOB87dszoOADg8I4ePaqFCxcyQx0AMxTOgh1bOKymTZtq165dOnnypFKlSmV0HLyi6OhoeXp6qnz58lqwYIHRcQDAoTFDHQszFM6AHVs4pCNHjmjRokUaNGgQA9lBpEqVSoMGDdJPP/2kI0eOGB0HABwWM9TxMEPhDNixhUNq3Lix9uzZoxMnTjCUHUh0dLTy5cun0qVL66effjI6DgA4JGaoY2KGwtGxYwuHc/jwYS1evFiDBw9mIDuYuBXnxYsX6/fffzc6DgA4nN9//50Z6qCYoXB07NjC4TRs2FAHDhxQeHi4UqZMaXQcJLKYmBjly5dPJUuW1KJFi4yOAwAOpVGjRtq/fz8z1EExQ+HI2LGFQzl06JCWLl2qwYMHM5AdVMqUKTV48GAtXrxYhw8fNjoOADiMQ4cOacmSJcxQB8YMhSNjxxYOpUGDBjp48KCOHz/OUHZgMTExyp8/v7y8vLRkyRKj4wCAQ2CGOgdmKBwVO7ZwGAcPHtSyZctYaXYCcSvOS5cu1W+//WZ0HACwe8xQ58EMhaNixxYOo169ejp8+LCOHz+uFClSGB0HSSwmJkYFChTQBx98oGXLlhkdBwDsGjPUuTBD4YjYsYVD+PXXX7VixQoNGTKEgewkUqZMqSFDhmj58uU6ePCg0XEAwG4xQ50PMxSOiB1bOIS6devq6NGjOnr0KEPZiTx48EAFCxZUkSJFtHz5cqPjAIBdYoY6J2YoHA07trB7Bw4c0MqVK1lpdkIpUqTQkCFDtGLFCv36669GxwEAu8MMdV7MUDgadmxh92rXrq3jx4+z0uykHjx4oEKFCqlgwYJauXKl0XEAwK7Url1b4eHhOnLkCDPUCTFD4UjYsYVd27dvn1avXq2hQ4cykJ1U3IrzqlWrtH//fqPjAIDdiJuh7NY6L2YoHAk7trBrNWvW1KlTp3TkyBG5uroaHQcGefDggQoXLqx8+fJp9erVRscBALvADIXEDIXjYMcWdmvPnj1au3athg4dykB2cilSpNDQoUO1Zs0a7du3z+g4AGDz9u7dywyFJGYoHAc7trBbNWrU0NmzZ3X48GGGMvTw4UMVKVJEefPm1Zo1a4yOAwA2jRmKxzFD4QjYsYVd+uWXX7Ru3TpWmmHl6uqqoUOHau3atdqzZ4/RcQDAZjFD8W/MUDgCdmxhl6pVq6Y//viDlWbE8/DhQ7333nvKlSuX1q1bZ3QcALBJ1apV07lz53To0CFmKKyYobB37NjC7uzatUsbNmzQsGHDGMiIJ27Fef369dq9e7fRcQDA5sTNUHZr8W/MUNg7dmxhdwICAnThwgUdOnRILi6szSC+hw8f6v3331eOHDm0YcMGo+MAgE1hhuJ5mKGwZ/yLBruyc+dObdy4UcOGDWMg46lcXV01bNgwBQcHa9euXUbHAQCbwQzFf2GGwp6xYwu7UqVKFV26dEkHDx5kKOOZYmNj9cEHH+itt95ScHCw0XEAwCYwQ5EQzFDYK/5Vg934+eeftWnTJlaa8Z9cXFw0bNgwbdy4UTt37jQ6DgAYjhmKhGKGwl6xYwu74e/vrytXrujXX39lKOM/xcbGqmjRonr99de1adMmo+MAgKGYoXgRzFDYI/5lg13Yvn27tmzZwkozEixuxXnz5s3asWOH0XEAwDDMULwoZijsETu2sAu+vr66fv26Dhw4wFBGgsXGxqpYsWLKmjWrtmzZYnQcADAEMxQvgxkKe8O/brB5W7duVWhoqAIDAxnIeCEuLi4KDAxUSEiItm3bZnQcAEh2zFC8LGYo7A07trB5Pj4+unnzpvbv3y+TyWR0HNgZi8UiLy8vZcqUSSEhIUbHAYBkxQzFq2CGwp6wdAebFhYWprCwMAUGBjKQ8VJMJpMCAwMVGhqqrVu3Gh0HAJINMxSvihkKe8KOLWyWxWKR2WzWnTt3tG/fPoYyXprFYlHx4sWVPn16hYWFGR0HAJIcMxSJhRkKe8GOLWxWaGiotm3bxkozXlncinPc75oBgKNjhiKxMENhL9ixhU2yWCyqWLGioqKitGfPHoYyXpnFYlHJkiXl4eGhrVu38ncKgMNihiKxMUNhD9ixhU3asmWLduzYwUozEk3civP27dtZcQbg0EJCQpihSFTMUNgDdmxhcywWiypUqKCYmBjt3r2boYxEY7FYVLp0abm5uWnbtm383QLgcJihSCrMUNg6dmxhczZv3qyff/6ZlWYkurgV5x07dvBm8wAcEjMUSYUZClvHji1sisViUfny5RUbG6tdu3YxlJHoLBaLypQpoxQpUmjHjh38HQPgMJihSGrMUNgydmxhUzZu3Khdu3ax0owkE7fivHPnTm3atMnoOACQaJihSGrMUNgydmxhMywWi8qWLSuTyaSdO3cylJFk+LsGwNHw7xqSC3/XYKvYsYXN2LBhg3755Rd9/vnn/COJJGUymfT5559r9+7d2rhxo9FxAOCVBQcHM0ORLJihsFXs2MIm8DsbSG78LhoAR8EMRXJjhsIWsWMLm7B+/Xrt2bOHlWYkm7gV519++UUbNmwwOg4AvDRmKJIbMxS2iB1bGM5isahUqVJyc3PT9u3bGcpINnHv9xgdHa1ffvmFv3sA7E7cDHV3d+e9RZGsmKGwNezYwnBr167Vvn37WGlGsot7dce9e/dq3bp1RscBgBcWN0N5JWQkN2YobA07tjCUxWJRyZIl5eHhoa1btzKUkewsFosqVqyoqKgo7dmzh7+DAOwGMxRGY4bClrBjC0OtWbNG+/fvZ7cWhon7PaF9+/Zp7dq1RscBgARjhsJozFDYEnZsYRiLxaISJUooXbp0CgsLMzoOnJjFYpHZbNY///yjvXv38gMiAJvHDIWtYIbCVrBjC8OsWrVKBw4cUGBgoNFR4OTiVpz379+v1atXGx0HAP5T3Az9/PPPjY4CJ8cMha1gxxaGsFgs8vLyUsaMGRUaGmp0HECS5OPjo5s3b2r//v2sOAOwWXEzNFOmTAoJCTE6DiCJGQrjsWMLQ6xYsUIHDx5kpRk2JTAwUL/++qtWrlxpdBQAeKa4GcoZT7AlzFAYjR1bJLvY2FgVK1ZMWbNm1ZYtW4yOA8Tj6+ur69ev68CBA3JxYe0PgG1hhsKWMUNhJP7GIdmtWLFChw4dYrcWNunzzz/Xb7/9xoozAJvEDIUtY4bCSOzYIlnFxsaqaNGiev3117Vp0yaj4wBP5e/vrytXrujXX39lxRmAzWCGwh4wQ2EU/rYhWS1btkyHDx/m94Jg0wIDA3Xo0CEtX77c6CgAYMUMhT1ghsIo7Ngi2cTGxuqDDz7Qm2++qY0bNxodB3iuypUr69KlS/rtt99YcQZgOGYo7AkzFEbgbxqSzZIlS/T777/ze0GwC59//rl+//13LV261OgoAMAMhV1hhsII7NgiWTx8+FDvv/++cuTIoQ0bNhgdB0iQgIAAXbhwQYcOHWLFGYBhmKGwR8xQJDf+liFZLFmyREePHmWlGXbl888/15EjR7RkyRKjowBwYsxQ2CNmKJIbO7ZIcg8fPtR7772nXLlyad26dUbHAV5ItWrVdO7cOR06dEiurq5GxwHgZJihsGfMUCQndmyR5BYtWqRjx47xKo6wS4GBgTp69KgWL15sdBQATogZCnvGDEVyYscWSerhw4cqUqSI8uTJo7Vr1xodB3gp1atX19mzZ/X777+z4gwg2TBD4QiYoUgu7NgiSS1cuFDHjx9npRl2LTAwUMePH9dPP/1kdBQAToQZCkfADEVyYccWSebBgwcqXLiw8uXLp9WrVxsdB3glNWvW1KlTp3TkyBFWnAEkuYcPH6pQoULMUDgEZiiSAzu2SDILFy7UiRMnWGmGQwgMDFR4eLgWLlxodBQATmDBggXMUDgMZiiSAzu2SBIPHjxQoUKFVLBgQa1cudLoOECiqF27tsLDw3XkyBGlSJHC6DgAHBQzFI6IGYqkxo4tksT8+fN18uRJVprhUAIDA3XixAktWLDA6CgAHBgzFI6IGYqkxo4tEt2DBw9UsGBBFS5cWCtWrDA6DpCo6tSpo6NHj+rYsWOsOANIdMxQODJmKJISO7ZIdEFBQTp16hQrzXBIgYGBOnXqlObNm2d0FAAOiBkKR8YMRVJixxaJKiYmRgUKFNAHH3ygZcuWGR0HSBL16tXT4cOHdfz4cVacASSaBw8eqECBAnr//feZoXBYzFAkFXZskaiCgoJ05swZVprh0AIDA3X69GkFBQUZHQWAA5k7d65Onz7NDIVDY4YiqbBji0QTExOj/Pnzy8vLS0uWLDE6DpCkGjRooIMHD+r48eNKmTKl0XEA2DlmKJwJMxRJgR1bJJo5c+bo7NmzGjZsmNFRgCQ3bNgwnTlzRnPnzjU6CgAHwAyFM2GGIimwY4tEER0drfz586tEiRJavHix0XGAZNGwYUMdOHBA4eHhrDgDeGnMUDgjZigSGzu2SBSzZ8/WH3/8wUoznMqwYcN09uxZzZ492+goAOwYMxTOiBmKxMaOLV5ZdHS03n33XZUpU0Y//fST0XGAZNW4cWPt3btX4eHhSpUqldFxANiZ6Oho5cuXT6VLl2aGwukwQ5GY2LHFK5s1a5b+/PNPVprhlIYNG6Y//viDFWcAL2XWrFk6d+4cMxROiRmKxMSOLV5J3G5tuXLltGDBAqPjAIZo2rSpdu3apZMnT7LiDCDBmKEAMxSJhx1bvJIZM2bozz//1NChQ42OAhhm6NCh+vPPPzVz5kyjowCwI8xQgBmKxMOOLV7a/fv35enpqQoVKmj+/PlGxwEM1axZM/388886efKk3NzcjI4DwMYxQ4H/wwxFYmDHFi9t+vTpunjxIivNgB6tOJ8/f14zZswwOgoAO8AMBf4PMxSJgR1bvJT79+8rb968MpvNCgoKMjoOYBNatGihbdu26dSpU6w4A3gmZijwJGYoXhU7tngp06ZN019//cVKM/CYoUOH6uLFi5o+fbrRUQDYMGYo8CRmKF4VO7ZIsIcPH2r79u0qU6aM8ubNKz8/P82ZM8foWIBNadWqlUJDQ3Xq1Cnt3r1bFSpUkKurq9GxABiMGQr8N2YoXgU7tkiwsLAw+fj4aOzYsbp06ZKGDBlidCTA5gwZMkR//fWXxo0bJx8fH4WFhRkdCYANYIYC/40ZildBsUWC3b9/X5L03XffqW7duho5cqTOnDljcCrAdpw+fVpffvml6tSpo++++07So/epBABmKPB8zFC8KootEizurPUrV65o8+bNCg0Nlbu7u8GpANuROnVqhYaGasuWLbp8+bKk/3veAHBuzFDg+ZiheFUUWyRY3GqzxWKRr6+vfv31V7311lsGpwJsx1tvvaVff/1Vvr6+1mEc97wB4NyYocDzMUPxqii2eGFDhgzRsmXLlClTJqOjADYnU6ZMWrZsmfX351htBvA4ZijwbMxQvApeFRkv5MGDB0qRIoXRMQC7wPMFwOP4NwFIOJ4veFEUWwAAAACAXeNUZAAAAACAXWN//1/OnTunq1evGh0DiShr1qx65513jI6BRMDz0/Hw/HQsPEcdD89Rx8Hz0/Hw/IyPYvuYc+fOqWDBgrp7967RUZCIPDw8dOzYMZ74do7np2Pi+ek4eI46Jp6jjoHnp2Pi+RkfxfYxV69e1d27dxUUFKSCBQsaHQeJ4NixY2rZsqWuXr3Kk97O8fx0PDw/HQvPUcfDc9Rx8Px0PDw/n0SxfYqCBQvKy8vL6BgAnoLnJ2DbeI4CtovnJxwZLx5lYzw9PSVJBw8e1FdffZWsjz1w4EDlzJlT/v7+z71deHi4UqZMqR07dkiSpk6dKrPZLLPZrAIFCqhBgwbxbj906FDr5wU4AiOen/8WGBioggULWp970dHR8a4/d+6c9Tqz2ayUKVMqMjJS0dHRaty4sSpUqKBSpUpp06ZNkqQpU6aoVKlSqlixopo1a6b79+8b8WkBicIWnqOdO3e2Pv/eeOMNjR8//onblCtXTpUqVVLJkiW1YMECSY/et7NDhw6qWLGiqlatqgsXLkiSZsyYIW9vb1WsWFG1atXSrVu3kvXzAV5GRESEVq1a9ULH3LhxQ3PmzLH+edasWdZZlVxu3rypMmXKKGPGjAoKCrJefubMGVWsWNH63P7jjz+eOLZBgwaqVKmSSpQooXHjxiVnbFhgtX//fosky/79+w3LkDdv3kS5n9u3b7/wMRcuXLCcPn3a4ufn99zbNW3a1OLv72/Zvn37E9d16NDB8tNPP1n/fP78eUvTpk0T7fN6UbbwPUXisJXv5YMHDxL9Pu/evWt5+PDhCx0zbNgwy9y5cxN0259//tlSrVo1i8VisaxevdrStm1bi8VisZw7d87i5eVlsVgslpMnT1oz9OnTxzJt2rQXyvMybOV7isRhK99PW3mOPq5gwYKWixcvPnH5/fv3LRaLxXLz5k1Lrly5LBaLxbJ8+XJLx44dLRaLxbJ9+3ZL69at493WYrFYhgwZYpkwYcJL50koW/me4tUZ9b0MDQ21fPTRR0+97lnP1bNnz/7nz6Iv6kV/Lo6OjrZcunTpiVn72WefWWbNmmWxWCyWuXPnWnr16vXEsXHP1ZiYGIunp6fl1q1br5D82Xh+PokdW4PFxsbqww8/VIUKFdS+fXvFxMRIksLCwtS+fXtJ0ogRI1SqVCn5+vpq7Nixz7yvO3fuKCgoSLVq1VLv3r1fOMtbb70lF5fn/5XYtm2bcuXKpbfffvuJ66KiorRx40bVrl3bellgYKAGDx78wlkAIw0aNEhly5aVj4+Pli5dqoiICJUsWVKtW7dWy5Yt4z0/27Ztq48//lg1a9ZUiRIltGzZMlWrVk2FCxfWzp07n/kYDx8+1KZNm9S2bVtVrVr1pXZIx4wZI29v7/9cEZ4zZ45atWolScqbN6/u378vi8WiyMhIvfbaa5IenS0S9/x3c3OTq6vrC+cBkou9PEclaffu3cqRI4fefPPNJ65LlSqVJOn27dsqXLiwJOnEiRMqUaKEJKlEiRIKDQ2Nd1vp0byPuz1gCyIiIlS8eHE1adJEpUuX1tChQyVJY8eO1dq1a2U2m7Vjxw61bdtWnTp1Uq1atRQcHKyBAwfK19dXXl5emjx5svWY/fv3y2w2a8mSJQoMDLTums6cOVOlS5dWmTJlNGrUqOdmOnXqlIYPHy5vb2+FhYW90OeTMmVKvf76609cXrhwYd24cUOSdP36desMfVzcc/Xu3bt655135OHh8UKPjZfH79gabNWqVUqRIoW2b9+ukydPau7cuU/cZt68edq3b5/SpEmj2NjYJ67fuHGj5syZo6tXr6p27dqaMWOGsmXLJknas2eP+vbt+8QxXbt2VcOGDV8oq8Vi0ciRI7Vw4UL16NHjietXr14tf39/ubu7S5IOHTokSQxf2JX169fr9OnT2rlzp0wmkx4+fKg///xTERER2rx5szJkyPDEgCxUqJCmTp2qESNGaO7cuVq/fr127Nih77//XuXKlYt326NHj2ratGk6cOCAzGazBgwYoPz580uSoqOjVaVKlScyeXt7a8SIEfEu69atm4YNG6b79++rTp06Klq0qHx8fJ44Njo6WuvXr7eW3zx58uju3bsqUKCAbty4oZUrV8a7/bFjx7R+/Xpt3br1hb92QHKwl+donLlz51oXlv7t3r17CggI0JEjR6w/pBcpUkQzZ87URx99pA0bNuj69evW20+ePFkTJ06Uh4eHBgwYkOCvGZAcIiIitGXLFqVPn15+fn76/fff1atXLwUFBWnatGmSpGnTpil79uzWElupUiWlSZNG9+/f13vvvaf27durV69eOnr0qDZv3ixJ+v333yVJV65c0bhx47R3716lSJFCvr6+qlWrVryfM+/cuaNZs2Zp9erVeuONN9S0aVMNHDhQKVI8qjzDhw9XSEjIE9nXrFmjtGnT/ufn6Ofnp4CAAE2fPl1RUVHas2fPU29Xp04d7dq1S506dWKhOBlRbA0WHh6uMmXKSJLeffddayF93IQJE9SlSxc9ePBAn3zyiby9veNdP2/ePJ0+fVrdunVT7dq14z0xS5Uq9cKrVM+ycOFC+fv7K2PGjE+9fs6cOfF2iocOHaoJEyYkymMDyeXw4cPy8/OTyWSSJOtAKlKkiDJkyPDUY4oXLy5Jyp49uywWi/Xja9euPXHbkJAQrVu3Th07dlSTJk301ltvWa9LlSpVgp+vWbJkkSS5u7urQYMG2rdv31OL7erVq+Xr66vUqVNLevS7StmzZ9eKFSsUERGhevXq6ddff5X06IeSNm3aaNGiRUqTJk2CcgDJzV6eo9KjIrx27VqNGTPmqdenTp1a27Zt09WrV1WyZEk1btxY1atX186dO2U2m1WyZEkVKFDAevtOnTqpU6dOGjVqlL766qtn3i9ghIIFC1p/RixdurTCw8Ots+pxj/8cO3nyZK1YsUKurq66fPmyLl++/Mz7P3PmjN5//325ublJksqUKaPw8PB4xfbixYuaOnWqSpcurXbt2qls2bLx7mPo0KHW3eSX0a9fP/3vf/9Tw4YNtXDhQg0YMMBa0h+3cuVK/fPPP6pYsaKaNGmiQoUKvfRjIuEotgbLly+f1q9fr48++kinT5/WlStXnrhN2bJl5efnp3PnzqlevXrav39/vOtnz56ta9eu6aefflK9evWUNWtWtW3bVgEBAYm6Y3vw4EHt27dPmzdv1uHDh3X8+HHNnz9fefLk0ZUrV3Ts2DFVrFjRevvTp09bTwX766+/1KVLF02cOPGFHhNIbkWKFFFQUJDat29v3Q2S9NwV17gfsP/9cdwP0I/r2rWrOnTooDVr1qh79+76559/VL9+fbVr104PHz5M8G7QjRs3lDFjRlksFoWGhqpZs2ZPzTZ37lx179493mVxC2iZMmXSnTt3JEmXLl1So0aNNH36dOXJk+eZnytgNHt5jkrSunXrVLFixacuFEVHRytFihRycXFRmjRp5O7ubj3jKe6+goODrac1RkVFWa/PlCmToqKinvn5AkY4duyYbt68qfTp02vPnj1q0aKFbt++rQcPHsS7XdxzNTIyUjNnztShQ4f+X3t3Hh/T2fYB/JcEiVgTuyIhEbtaguw5kwQtStVSS6kqquj66qot9ah6uz1P91KeKlrdUUqpOicEsSQlQVBLqvYtQUT2+/0j75xmZBJZZuacM/l9P59+yqz35HLnmuu+7nMOcnNz0a5dOwghUKNGjWLPAQp3HO3fvx/Z2dmoXr064uPjMX78eIvHBAQEICkpCfv27cOKFSvw3HPPITw8HFOnToWPj0+lO7bAPzm0UaNG6rZks4KCAuTn56N69eqoWbOm+h85BgtbjQ0ZMgSrV69GeHg4OnfubPUYnKFDhyIrKwtZWVmYPn261ddp0KABpk2bhmnTpuHkyZPqGYvL07F9//338f333yMlJQUxMTH45JNPEBAQgLFjx+Krr77C//7v/6qPnTBhAiZNmqR+Af7mm28wcuRIiy8MycnJ6p/9/f1Z1JIhDBgwALGxsQgODoanpyemT5+udntsxd3dHcOGDcOwYcOQnp6O77//Hjk5OahZs2aZ5+vTTz+NI0eOQAiB8PBw9dj2p59+GrNmzUKjRo1w5coVJCUlQZIk9XkPPfQQRo8ejcjISGRmZuKNN94AALz44ou4cOGCWgSPGTMGU6ZMsennJrIFo8xRoHBh6bHHHrO4zTxHr127hokTJ8LNzQ3Z2dmYPXs23N3dkZaWhqFDh8LNzQ0+Pj7qzqe5c+eqxwR7e3vjv//9r80+L5EttGnTBo8//jiOHz+OmJgYdOnSBTdu3MDx48cxfPhwvPDCCxaPr1+/Pjp27IiwsDB07NhR7e42bdoUNWvWxLBhwzBx4kT18Y0aNcJTTz2F8PBwuLi4YPDgwSUe7tatWzd069YNBQUFkGUZZ8+ehY+PT7k6tgMGDMDhw4fh6emJ2NhYfP7553jllVfw2GOPoVq1asjNzcXChQsBAAsWLMDAgQPh6+uL++67DwCQnZ2NUaNGoXXr1uX+WVLFuAhry5VVVGJiInr27ImEhARe48tJMKbOg7F0Poypc2E8nQ9j6jzsHcvU1FRMmjRJPS6W7I/zszieFZmIiIiIiIgMjYUtERERERFVmK+vL7u1pDkWtkRERERERGRoLGwNoujFqfVuzZo16NOnDyIjIzFw4ED1cgrZ2dkYP348wsPDcf/99+PatWvFnvvAAw9AkiRIkoT69etj7dq1OHXqlHqbJEmoXr060tLSABReliEmJgYmk4nX9CNNGWmOHj16FD169EDt2rXVE80BQH5+Pl566SXExMRAkiSr17JNSkpCWFgYQkJC8O6771rcl5OTA39/f4uzw86ePRshISGQJEm9FiGRoxlpfppt2bIFLi4uOH36tMXtS5YsQfXq1a0+58MPP0RAQAD8/f2L3Xf7/Ny9e7eaV4OCgqxeloXIUZxhji5cuBC9e/dGREQERo8ejezs7GLP+fvvvxETE4Pw8HCLS2QOGzYMkZGRCAwMVK87DwAxMTFo1KhRidfJJkssbDVmvkyBI99HCGH1EgelPac87r77bsTFxSE2NhYDBw7Ef/7zHwCFlyXy9fXFtm3bMGDAALz33nvFnvvTTz9BURT8+uuvqF+/Pvr164dWrVpBURQoioL58+ejb9++8PLywpUrV/Duu+/il19+gSzLePPNNys0XqLSOOMcbdGiBX7//fdil/xavHgxWrZsic2bN0NRFERGRhZ77vTp0/HFF18gLi4Oa9aswfHjx9X7Pv74Y4tr9e3btw+7d+/Gjh07sHTpUjz11FMVGi9RSZxxfgKFlwx55513EBgYaHF7ZmYmfvrpJ7Rq1crq80aOHImDBw9ave/2+Wm+aoKiKHjyySfx4IMPVni8RCWpSnM0Ojoa8fHx2Lp1K1q2bGm1UH/hhRfw8ssvY9u2bTh79ixkWQYArFy5ErGxsYiPj8cnn3yCGzduACi89vzbb79d4XFWNSxsS5GamorQ0FCYTCZIkoS0tDRcuHAB0dHR6NevH6ZNm4aYmBgAhZe/MXc+FEVRr9/6/vvvIyoqCoGBgXjllVfU1/bx8cH06dPRr18/XLt2DSNHjkRUVBRMJhOOHj0KAFi1ahW6deuGwYMHF7t2bVG5ubmYPHkyoqKiEBYWhp07d6pjevzxx3Hfffdh48aN8Pf3x6xZsxAdHY3Tp09j1KhRiIyMRGhoqPr6tz+nInx9fdXVZHd3d/V6ZbIsY+jQoQCA+++/X53M1qxevRr9+/dXL8JttmzZMowbNw4A8Msvv6BRo0a4//77ERMTg/j4+AqNl4yLc7Ric9TT0xNeXl7Fbv/2229x7tw5REVFYeLEiWpiNcvOzsb169fRtm1buLq6YtCgQWpXNz09HZs3b8YDDzygPv7o0aPqZVh8fX2RkpJi9dqE5Jw4Pys2PwFgxYoVGDx4cLHr377zzjt44oknLC6tV1STJk2sdnOtzc+iiuZWqjo4R207R/39/eHqWlhaFf3+W1RiYiKioqIAWH4XNl+vOjMzE61atYKnpyeAwoVoKjsWtqXYsmUL+vbtC1mWoSgK6tevjzfffBMTJ07Epk2biq2kWjNp0iRs2bIFe/bswe+//46//voLAHD27Fk899xz+P333/Hmm2/igQcewJYtW/DRRx/h+eefR0FBAV588UXExsZi9erVxb5gFrVkyRL4+flhy5YtWLVqFZ599ln1vhYtWmDt2rUYMGAA8vLyMGDAAGzZsgU//fQT2rdvj9jYWPz3v/+1uD5u0ecUNW3aNIstwZIkYdCgQSWO6/z58/joo4/Ua2FeuXJF/TJt7riWZPny5cWSbE5ODjZs2ID7778fAHDmzBmkpKRg1apVWLJkicW1zqhq4Byt3By93ZkzZ+Dt7Y0tW7agY8eOxVaJi85hwHIev/HGG8WuUdipUyfIsoycnBwkJibi/PnzxS5mT86L87Ni8/PWrVtYtmyZWjiYnT9/HgkJCbjnnnvu+HO7nbX5WfR1U1NTERwcXO7XJWPjHLXtHDVLSUnBhg0bMGLEiGL3FRQUqH++/bvwkCFD4O/vj7CwMKtFMd1ZNa0HoGcjR47E/PnzMXbsWPj4+GDOnDk4cuQInnjiCQBASEgIvv76awCwWD0tuv3hxx9/xOLFi+Hi4oKTJ0/i9OnT8PHxQYsWLeDr6wsASE5ORmxsLD777DP1tS5duoTGjRujXr16AICgoKASx5mcnIwdO3bg119/BQCLL45hYWHqn93c3BASEgIAOHz4MIYNGwYAaNeuncXEKvqcoj755JNSflqW0tLSMGzYMCxatAjNmzcHADRo0ABpaWnw9fVFenp6icfzXLhwAX/++SdCQ0Mtbl+7di2ioqJQs2ZNAIUXqDeZTPDw8ICPjw/q1q2Lq1evwtvbu8zjJGPjHLVUnjlqjbe3N+69914AwKBBg/D8888Xu7/o2M3zODU1FSdPnkRERAROnDih3t+pUyeMHj0aMTExCAgIQJcuXXgcXxXC+WmprPPzP//5D6ZOnYpq1Sy/os2ZM8eiI1ZWJc1Ps6+++gqjR48u9+uS8XGOWqrsHAUK59vDDz+M7777rtiOCwBqR9f8OYrmxDVr1uDmzZuIiIjAgw8+aHHoAJUNC9tSuLq6Yv78+QCAiRMnYuPGjQgICMCuXbvg5+dnsfXV29sbp06dAgDs2bNHvf3VV1/F4cOH4e7ujtDQUPWXQdGVmE6dOiE4OFjdppuTkwM3NzdcuHAB169fR506dbB792507tzZ6jg7deoEf39/PPPMM+rzzYq+j4uLi/qLqX379ti2bRtiYmJw5MgRi4lV0irRtGnTcOjQIYvbateujXXr1lnclpGRgSFDhuD1119Hr1691NslScLPP/+M7t274+eff4YkSVbfZ+XKlRg1alSxrVbLly/Hk08+qf7dZDLhxx9/hBAC165dQ1pamtXtleS8OEctlXWOliQ6Ohp79+5F+/btsWvXLgQEBFjc7+HhgTp16uDEiRNo3bo11q9fj88//xyJiYk4e/Ys7rnnHpw5cwbZ2dno3Lkz7r//fsyYMQMzZszAgQMH8Pbbb5e4hZKcD+enpbLOz4MHDyI2NhaLFy9GUlISxo0bh3Xr1uHYsWN49dVXAQDnzp3D8OHD8cMPP1h9r6JKm59A4ZbKsrwOOR/OUUuVnaM3btzAiBEjsGTJErRp08bqe3Tv3h2xsbGIjIzEzz//jEceeQQFBQXIz89H9erVUbNmTfU/Kj8WtqVYt24dPvzwQ7i5ucHd3R1hYWEIDAzEmDFj8MUXX1hMwEmTJmHMmDH4+uuv0bp1a/X2Bx54AKGhoWjfvj1q165t9X1mzZqFqVOn4sMPPwQA9O/fHy+88ALefPNNREREoGXLlqV2ISdPnowZM2bAZDIBKJw01k7MdPtzJkyYgIiICOTl5anvXZqyrmS98847OHz4MObNm4d58+YhKioKr732GiZMmIBJkyYhIiICXl5e+PLLLwEUHhh/1113oW/fvgAKC9iVK1davOaVK1eQlJRkUQwHBATg3nvvRWRkJLKzs/Hee+/xS3MVwzlqqaxzNC0tDSNGjMChQ4dw8OBB9O/fH/PmzcPMmTPx6KOPYsmSJfDw8MCyZcsAAAsWLMDAgQPRpUsXfPDBBxg/fjwKCgowdOhQ+Pv7w9/fXz12b+nSpTh9+rT6pblfv37Iy8tDw4YN8fHHH5dpfOQcOD8tlXV+Fj3hjCRJWL58OWrVqmVxjVB/f3+1GC2aQ7/55hssXrwYZ8+eRUxMDGbPno0HHnigxPmZnJwMT09P+Pn5lWls5Fw4Ry1Vdo5Onz4dFy5cUJswY8aMwZQpUyzm6IIFCzBx4kTk5OQgMDAQJpMJGRkZuO+++wAUnsti1KhR6s944sSJ2LVrF7Kzs7Fr1y6sXbu2TGOsqlxEWU4bVkUkJiaiZ8+eSEhIQI8ePe74+NTUVEyaNIkXpNax8saU9KsiseQc1TfOT+fCHOp8OEedB3Oo8+H8LI4dW4MZP368uhUEKNwa8tNPP2k4IiIqinOUSL84P4n0jXOUKoOFbSX4+vo6fBXLvDWQiO6Mc5RIvzg/ifSNc5SMhpf7cVL+/v4OeZ+4uDh06dIFHh4eOH36tHr7rVu3MHXqVMTExECSJBw5cgQ5OTkWp1D38PBAcnKyQ8ZJpCdaz88PP/wQAQEBFuM4deqUxfysXr060tLSHDJOIj1z1Hw1W7JkicW1aItegqRp06ZlOlaQqKpw1PxcuHAhevfujYiICIwePRrZ2dkACi+lFRERgdDQUIwfPx65ubkOGQ9Zx8KWKqVLly7YuXNnsdO0z507F4MHD8bmzZuhKAratWuHGjVqQFEUKIqCFStWwN/fH126dNFo5ETOr6T5OXLkSBw8eNDitlatWqnzc/78+ejbty/PMk7kYJmZmfjpp5/QqlUr9bZPPvlEnZve3t4YPny4hiMkqpqio6MRHx+PrVu3omXLluoJpJ577jls3boV27dvBwBs2rRJy2FWedyK7GCpqakYO3YsatSoASEEVq1aheTkZMyePRt5eXnw8vLCt99+i5o1a0KSJHTv3h2HDh1CdnY2pkyZgi+//BIXLlzAd999h4CAAEiShE6dOuHo0aMoKCjAypUr0bhxY/X9cnNzMW3aNBw/fhw5OTl4++23ERwcjHnz5uHnn39G7dq1MWjQIIuLXZeH+fpjt9u0aRPy8vLw1ltvoUePHnjrrbcsrve1YsUKjB07tkLvSWQvVWV+NmnSpNTnLVu2DOPGjavQexI5irPNV6DwqgJPPPEEZsyYUey++Ph4tGzZEs2aNavw6xM5irPNz6KdYXd3d/WSQTVq1AAAFBQUIC8vz+E7PMgSO7YOtmXLFvTt2xeyLENRFNSvXx89e/aELMvYtm0bOnTogO+++059fGRkJDZu3Ah/f3/s2bMHGzduxMyZM/Hf//5XfUyfPn3w22+/YezYsXj77bct3m/JkiXw8/PDli1bsGrVKnVCf/XVV5BlGVu2bMHTTz9dbJwPPPCAxbZESZIwadKkMn/OAwcOICQkBIqiIDc3t9gxE1999RULW9KdqjI/S5OTk4MNGzaolwMh0itnm6/nz59HQkIC7rnnHqufd/ny5VxwIsNwtvlplpKSgg0bNmDEiBHqbbNnz0ZAQADS09PRsmXLiv7IyAbYsXWwkSNHYv78+Rg7dix8fHwwZ84cHDx4EK+88gqys7Nx4cIF1K1bV318z549AQAtWrRQrzPXokULxMbGqo8JCQlR/79q1SqL90tOTsaOHTvw66+/AgDS09MBAB999BGmT5+OvLw8TJ06FWFhYRbPq+wZ6Ly9vXHvvfcCAAYOHIj169er9yUkJKBhw4YWW62I9KCqzM/SrF27FlFRUbw4POmes83XOXPm4JVXXrF6X05ODn755Re89dZbZXotIq052/wECrvQDz/8ML777jvUqlVLvf3111/HnDlzMH36dCxduhTTpk0r82uSbbGwdTBXV1fMnz8fQOFFlzdu3IjFixfj9ddfR3BwMJ5//nkUvbSwi4uL1T8XfUx8fDz8/f0RHx+Pdu3aWbxfp06d4O/vj2eeeQZAYXIEgODgYERHR+PUqVMYOnQoEhISLJ73wAMP4OrVqxa3+fv7Y/HixWX6nNHR0di7dy/CwsKwa9cuBAQEqPdx1Zn0qqrMz9IsX75cvbg8kZ4523w9duwYXn31VQDAuXPnMHz4cPzwww8AgPXr1yMiIsLiyzSRnjnb/Dx//jxGjBiBJUuWoE2bNurtWVlZ8PDwgIuLC+rVqwdPT8+y/5DI5ljYOti6devw4Ycfws3NDe7u7ggLC0NGRgYeffRRtG/fHnXr1rVYwSqLxMREfPnll8jPz8fKlSst7ps8eTJmzJgBk8kEAOjevTvee+89DB06FFlZWcjKysL06dOLvWZZV7BSUlLwxBNPYP/+/Rg9ejQefPBBzJgxAwsWLMCkSZOQlZWFxo0bq1uR8/LysHr1asydO7dcn5HIEarK/Pzmm2+wePFinD17FjExMZg9ezbCw8Nx5coVJCUlQZKkcn1GIi0423wtelkVf39/tagFChecHnvssXJ9FiItOdv8fPHFF3HhwgV14XfMmDGYMmUKpk2bhhMnTiA/Px8BAQH8fqsxF1F0KaSKS0xMRM+ePZGQkIAePXpoPZwykSQJK1asQIsWLbQeii4ZMaZknRFjyflZOiPGlEpm9HhyvhZn9JjSP4weS87P4oweU3vgyaOIiIiIiIjI0LgV2eAURdF6CERUAs5PIuPgfCXSL85PKgt2bImIiIiIiMjQWNjqVGpqKmJiYhz2fnPmzEGfPn0QGhqKJ598Uj0L3ZQpUxAUFISgoCAsWLDA6nMXLlyIPn36IDw8XF1Ry8nJwciRIxEeHo7evXvjt99+AwDExcWhS5cu8PDwwOnTpx3y2YjswdFz9IcffkCHDh3g4eFh9f6IiAir194TQmDGjBkIDg5Gr169sGLFCvX2Z599FuHh4YiJiVHn44kTJxAREaFez++vv/6y34cishNHz8833ngDERERCA0Nxfjx45GbmwsASEpKQlhYGEJCQvDuu+9afe7s2bMREhICSZJw4MABAMCaNWvQp08fREZGYuDAgbhy5QoA5lByDo6en2avvfYa/P39i90+fvx4q+M5deqUxfVtq1evjrS0NADA22+/jdDQUISHhyM5ORkAkJmZieHDh0OSJAwbNgzXrl2z7weiYljYEoDCs7vt2rUL27dvx/nz57FlyxYAwMyZMxEfH48dO3ZgzZo1OH78uMXzLl68iIULFyIuLg7r1q3DzJkzUVBQgE2bNqFWrVrYtm0bfvzxR7z44osAgC5dumDnzp0ICgpy+GckMjJJkvDHH39YPXHGqlWrUL9+favPO3jwIA4ePIidO3dCURS89tprAIDffvsNly9fxrZt2/D8889j1qxZAIBPPvkEjz76KBRFwaRJk/DBBx/Y7TMROYvnnnsOW7duxfbt2wEAmzZtAgBMnz4dX3zxBeLi4qzm0H379mH37t3YsWMHli5diqeeegoAcPfddyMuLg6xsbEYOHAg/vOf/wBgDiWqqDNnzuDPP/8sdntiYiKuX79u9TmtWrWCoihQFAXz589H37594eXlhaNHj2L9+vWIi4vD559/rp4pedGiRQgMDISiKBg6dCjee+89u34mKo6FrQPNnDkTP/74I4DCy9507doVubm5ePnllxEVFYUePXrg008/Lfa8CRMmIC4uDgDUL5sAcODAAcTExCAqKgojRoxAZmZmhcdW9Dqz7u7ucHNzs7jd1dUV1apVU283S01NRceOHVG9enXUq1cP1apVQ2pqKvz8/JCdnQ0hBNLS0tC4cWMAQL169VC7du0Kj5PInvQ8Rxs2bGi1W5uXl4dPP/3U6mUMAKB58+aoUaMGcnNzcePGDXh7ewMAZFnG0KFDAQB9+/bF7t27ARReC9B8YfurV6+qc5dIa3qenzVq1AAAFBQUIC8vD/7+/sjOzsb169fRtm1buLq6YtCgQYiNjbV43tGjR9GzZ08AgK+vL1JSUpCXlwdfX19Ur14dgGVOZg4lvdLz/AQKdya+8sorxW6fO3euurBbmmXLlmHcuHEACvPn4MGD4eLigvbt2+PSpUvIy8vD0aNHERgYCAAIDAyELMuVGjOVH08e5UATJkzAyy+/jGHDhmHjxo2IiopC9erVMWvWLNSqVQvZ2dno0qWL1e2E1kybNg0rVqxAq1at8PHHH2PRokV4+umn1ftzcnLQr1+/Ys8LCwvDvHnzrL6moig4ffo0IiIiLG5fsWIFWrZsCV9fX4vb/fz88Mcff+D69eu4fv06Dh48iKtXr6JLly7IzMxE+/btkZ6ejjVr1pTpMxFpyQhz9HafffYZHnroIbi7u1u938vLC35+fggICMDNmzexcOFCAMCVK1fg5eUFAHBxcUF+fj4AIDo6Gv3798eSJUuQlZWlFrxEWtP7/Jw9eza++uorBAQEoGXLlhZzDCici+YtxWadOnXC+++/j5ycHBw4cADnz59Heno6GjZsCAA4f/48PvroI/zyyy9l+kxEWtHz/ExKSgJQON+KWrduHXr06IFGjRqVOpacnBxs2LAB//73vwEU5s/mzZur99erVw9paWno3Lkzfv31V8TExODXX3/F1atXy/RZyXZY2DpQ586dcenSJVy8eBFffvklXnrpJQDAp59+itWrV8PNzQ0XL17ExYsXLZ7n4uKi/rnoZYcPHjyI8ePHAwCys7MhSZLF82rUqFGus8glJibipZdewrp16+Dq+k8zf8OGDVi2bBl+/vnnYs9p0KAB5syZg0GDBqFZs2bo1q0bmjdvjqVLl6JFixZYvXo1UlNTMXToUPzxxx9lHguRFvQ+R293/fp1rF69Gps2bcLWrVutPmbTpk04c+YMjh07hmvXriEsLAwDBgxAgwYN1GOFhBCoVq0wHbzwwgv417/+heHDh+Obb77BSy+9ZHWVncjR9D4/X3/9dcyZMwfTp0/H0qVLMXHiRHX3AwCkp6ejQYMGFs/p1KkTRo8ejZiYGAQEBKBLly7qY9LS0jBs2DAsWrTI4ks0kR7peX6+9tpr+Oijjyxuy8/Px3vvvYe1a9fi0qVLpT5/7dq1iIqKQs2aNQHAIn8ChbnYy8sLjz76KJ555hmYTCYEBwdz3mqAha2DjR07Fh9//DFSU1PRvXt3pKWl4YsvvkBSUhJyc3PRrl07i4kNAN7e3jh16hQAYM+ePertnTt3xsqVK9GsWTMAhStKRZVnNSslJQVTpkzB6tWrLRLv1q1bMW/ePKxfv77Ek9aMGDECI0aMwLlz5zBp0iR1IptXwLy8vJCRkVGmnw+R1vQ6R61JSUnB9evXMWDAAFy9ehXnzp3DwoUL8dhjjxUbn5ubG+rUqYPc3Fzk5+dDkiR88803GDp0KLZs2aJunwL+mbuNGjWy+GJOpDW9zs+srCx4eHjAxcUF9erVg6enJzw8PFCnTh2cOHECrVu3xvr16/H5558Xe70ZM2ZgxowZOHDgAN5++224uLggIyMDQ4YMweuvv45evXpV7IdF5GB6nZ/Hjx9XO8Xnzp3D9OnT8fLLL6uLR7du3cLBgwcxd+5c9TwURS1fvlw9jhYoPOfF9OnT8fTTT+PYsWNo0KABqlWrhmrVquGTTz4BUHhi1dt3OZIDCFIlJCQIACIhIcFu73HlyhXh6ekp3nnnHSGEEAUFBWL48OEiKChITJw4UXTv3l38/fff4uTJkyI6OloIIcShQ4dEt27dxMCBA8WMGTPEo48+KoQQIjk5WfTr10+YTCZhMpnEhg0bKjyuyMhI0bZtWxEZGSkiIyPFmjVrhBBC+Pj4iC5duqi379q1SwghxFNPPSUuXrwohBBi3LhxQpIkMXDgQHH8+HEhhBAZGRnivvvuExERESIwMFB8++236meJjo4W9evXF2FhYeLDDz+s8JjLwhExJcdwVCz1OkdlWRbR0dGiZs2aIjo6Wnz33XfF7je/rxBCjBkzRgghRF5ennj44YdFSEiICAwMFO+//776uZ566ikRFhYmoqOjxalTp4QQQhw4cECEhoaKyMhIERISIpKTkys85jvh/HQuVTmHPvLIIyIyMlKEhYWJiRMnipycHCGEEImJiSI0NFQEBweLt956S328eX4KIUTfvn2FyWQSI0aMUPPq7NmzRaNGjdTc+/rrr6ufhTmUKqIqz8+i/Pz8it1WdDxCWH7HvXz5smjdurXIz8+3eM6CBQtESEiICA0NFfv27RNCCHHw4EERGRkpoqKixLPPPivy8vJsMuaScH4W5yLEbUsnVVhiYiJ69uyJhIQE9OjRQ+vhkA0wps6DsXQ+jKlzYTydD2PqPBhL58OYFsezIhMREREREZGhsbAlIiIiIiIiQ2NhS0RERERERIbGsyJbkZKSovUQyEYYS+fDmDoPxtI5Ma7Og7F0Poyp82Asi2NhW0TDhg3h6emJhx56SOuhkA15enqqF7sn4+L8dE6cn86Dc9Q5cY46B85P58T5aYlnRb7NqVOncPnyZa2HYROPPvoovLy88M4775Tp8X/++SdGjRqFzz77zKmum9ewYUO0atVK62GQDTjT/Ny9ezcef/xxfPvtt/D39y/Tc2bOnIn09HQsXrzYzqNzHM5P5+JMc3TSpEnw8vLC22+/XabHM4eS3jnT/GQOLcT5aYmFrZPKzMxE/fr18d5772HGjBllek5BQQEaN26MadOmYe7cuXYeIVHV9uqrr+Kzzz7DhQsX4OpattMdfPjhh2pirlmzpp1HSFR1MYcS6RtzKFnDk0c5qZ07dyI3NxeSJJX5Oa6uroiMjISiKHYbFxEVUhQFkZGRZU7IACBJEnJycrBz5047joyImEOJ9I05lKxhYeukZFlGw4YN0alTp3I9z2QyIT4+HpmZmXYaGRFlZmZi165dMJlM5Xpep06d0LBhQ8iybKeRERHAHEqkZ8yhVBIWtk5KURRIkgQXF5dyPU+SJOTm5nI1i8iOduzYUe5uEMCOEJGjMIcS6RdzKJWEha0TunnzJnbv3l3ulSzgn9UsTnoi+1EUBY0aNULHjh3L/VyTyYRdu3axI0RkJ8yhRPrGHEolYWHrhCq6kgUALi4ukCSJ2zSI7EiW5Qp1g4B/OkI7duyww8iIiDmUSN+YQ6kkLGydkKIoaNy4MTp06FCh50uShN27d+PmzZs2HhkRmbtBFfnSDAAdO3ZEo0aN2BEishPmUCL9Yg6l0rCwdUKVWckCCrdpcDWLyD62b9+OvLy8Cm1zBNgRIrI35lAi/WIOpdKwsHUyGRkZ2LNnT4VXsgCgQ4cOaNy4MVeziOxAURQ0adIE7du3r/BrsCNEZB/MoUT6xhxKpWFh62Qqu5IFcDWLyJ4q2w0CCjtCeXl52L59uw1HRkTMoUT6xhxKpWFh62TMK1nt2rWr1OtIkoQ9e/YgIyPDRiMjIlt0gwCgffv2aNKkCTtCRDamKAqaNm3KHEqkQ8yhdCcsbJ2MLVaygH9Ws3iMEJHtbN++Hfn5+ZXqBgH/dISYlIlsq6LXr70dcyiR7TGH0p2wsHUiN27cwN69eys94QGgXbt2aNKkCbdSEdmQLMto2rQpAgICKv1a7AgR2daNGzds0g0CmEOJ7IE5lO6Eha0TMa9k2SIpczWLyPZs1Q0CCpMyjxEish3mUCJ9Yw6lO2Fh60RkWUazZs1sspIFFG6l2rNnD27cuGGT1yOqymy5owIo7Ag1bdqUHSEiG2EOJdIv5lAqCxa2TsSWK1lA4WpWfn4+V7OIbCAuLs5m3SCAHSEiW2MOJdIv5lAqCxa2TuL69etISEiw2UoWAAQEBKBZs2ac9EQ2oCgKmjdvjrZt29rsNU0mE/bu3cuOEFElMYcS6RtzKJUFC1snYeuVLIDX4iOyJVudsbwoc0coLi7OZq9JVBUxhxLpG3MolQULWychyzKaN28Of39/m76uJElISEjA9evXbfq6RFWJuRtkyy/NANC2bVt2hIhswNwNYg4l0h/mUCorFrZOQlEUmEwmm65kAYXbNLiaRVQ527ZtQ0FBgU23OQKFHSGTycSOEFElybLMHEqkU8yhVFYsbJ3AtWvXkJiYaPOVLADw9/dH8+bNuZpFVAmKouCuu+6Cn5+fzV+bHSGiymEOJdI35lAqKxa2TsBeK1nAP6tZTMpEFWevHRVAYUeooKCAHSGiCoqLi2MOJdIx5lAqKxa2TkBRFLRo0QJt2rSxy+ubV7OuXbtml9cncmb27AYBgJ+fH+666y5upSKqIFmWmUOJdIo5lMqDha0TsMeZ4oriahZRxdlzRwXAjhBRZdmzGwQwhxJVBnMolQcLW4NLT0/HH3/8YbcJDwBt2rRBixYtuJpFVAGyLKNly5Zo3bq13d5DkiQkJiayI0RUTuYcaq9uEMAcSlQZzKFUHixsDW7btm0QQtg1KZuvxcfVLKLyUxTFrjsqgMKkXFBQgG3bttntPYickbkbxBxKpE/MoVQeLGwNTpZltGrVyq4rWUDhVqo//vgD6enpdn0fImeSlpZm9x0VQGFHqGXLluwIEZUTcyiRfjGHUnmxsDU4R6xkAVzNIqoIR+yoANgRIqoo5lAi/WIOpfJiYWtgV69exb59++y+kgUArVu3RqtWrTjpicpBURT4+PjYvRsEsCNEVF5paWnMoUQ6xhxK5cXC1sActZIF/LOaxW0aRGVnPmO5I0iSBCEEtm7d6pD3IzK6rVu3MocS6RhzKJUXC1sDk2UZPj4+8PX1dcj7SZKEffv2IS0tzSHvR2RkV69exf79+x2WlH19fdkRIioHczeIOZRIf5hDqSJY2BqY+dp7jmIymbiaRVRGjuwGAf9ci48dIaKykWWZOZRIp5hDqSJY2BrU1atXkZSU5LAJDxSuZvn4+HA1i6gMFEWBr6+vw7pBQGFHaP/+/bh69arD3pPIiJhDifSNOZQqgoWtQcXGxjp0JcvMZDIxKROVgaN3VAD/HCPEM68Slc7R3SAz5lCismEOpYpgYWtQiqKgdevW8PHxcej7cjWL6M6uXLni0GODzMyr29xKRVQ6WZaZQ4l0ijmUKoqFrUE58kxxRfGscUR3Zp4fWsxRdoSI7kyLbhDAHEpUFsyhVFEsbA3o8uXLSE5O1iQpm68nxtUsopLJsow2bdqgVatWDn9vc0foypUrDn9vIiO4fPmyw4+vNWMOJboz5lCqKBa2BqTlSpb5fbmaRVQyRVE0nZ8A2BEiKgFzKJG+MYdSRbGwNSBZluHn54eWLVtq8v4mkwlJSUlczSKyQssdFQDQqlUrtGnThl+ciUqgKApzKJFOMYdSZbCwNSAtV7KAf1azYmNjNRsDkV6Z54XWc5RbHYms0+ocFWbMoUQlYw6lymBhazCXLl3CgQMHNFvJAoCWLVvCz8+Pq1lEViiKAn9/f7Ro0UKzMZhMJiQnJ+Py5cuajYFIj5hDifSNOZQqg4WtwZhXsiIjIzUdB1eziKzTuhsEsCNEVBI9dIPM788cSlQccyhVBgtbg5FlWfOVLKBwNevAgQO4dOmSpuMg0pOLFy/i4MGDmnaDAKBFixbw9/dnR4joNoqioG3btrjrrrs0HQdzKFFxzKFUWSxsDUara+/dztwx5lnjiP5hng9a76gAeOZVImu0PkeFGXMoUXHMoVRZLGwN5OLFizh06JAukrJ5NYtbqYj+IcuyLrpBQGFSZkeI6B/mbhBzKJE+MYdSZbGwNRDzypEekjJQuJWKq1lE/9DLjgqAxwgR3U4vx9eaMYcSWWIOpcpiYWsgiqIgICAAzZs313ooAAon/cGDB3Hx4kWth0KkuQsXLuhmRwUA3HXXXWjbti07QkT/T5Zl5lAinWIOJVtgYWsgejhTXFFczSL6h966QQA7QkRF6akbBDCHEhXFHEq2wMLWIM6fP4/Dhw/rKik3b94cAQEBXM0iQuHCU7t27dCsWTOth6KSJAmHDh3ChQsXtB4KkabOnz+PlJQUXX1pZg4l+gdzKNkCC1uD0Mv1a2/Hs8YRFdLL2VaLYkeIqBBzKJG+MYeSLbCwNQhZltG+fXtdrWQBhds0UlJSuJpFVZoed1QAQLNmzdCuXTt+caYqT1EU5lAinWIOJVthYWsQelzJAv5Z/eakp6rM/O9fb90goHDFmVsdqarT2zkqzJhDiZhDyXZY2BrA2bNnceTIEd2tZAGFq1nt27dnUqYqTVEUdOjQAU2bNtV6KMWYTCYcPnwY58+f13ooRJo4d+4ccyiRjjGHkq2wsDUAvR4bZMbVLKrq9NoNAtgRItJzNwhgDiViDiVbYWFrALIso0OHDmjSpInWQ7HKZDLhyJEjOHfunNZDIXK4s2fP4ujRo7rsBgFA06ZN0aFDByZlqrIURUHHjh2ZQ4l0iDmUbImFrQHo7dp7tzOvZvGscVQV6X1HBcAzr1LVptdzVJgxh1JVxhxKtsTCVufOnDmDP//8U9dJuUmTJujQoQO3UlGVJMsyOnbsiMaNG2s9lBJJkoQjR47g7NmzWg+FyKHM3SDmUCJ9Yg4lW2Jhq3N6PzbIzGQycTWLqiS976gAeC0+qrqYQ4n0jTmUbImFrc4pioJOnTrpeiULKJz0R48e5WoWVSlG2FEBAI0bN0bHjh3ZEaIqR5Zl5lAinWIOJVtjYatzej5TXFE8axxVRUbpBgHsCFHVZIRuEMAcSlUTcyjZGgtbHfv7779x/PhxQyTlxo0bo1OnTpz0VKUoioLOnTujUaNGWg/ljiRJwp9//okzZ85oPRQihzh9+jSOHTtmiMVh5lCqiphDydZY2OqYEc4UVxSvxUdVjVF2VADsCFHVY6RuEMAcSlUPcyjZGgtbHZNlGV26dEHDhg21HkqZmEwmHDt2DKdPn9Z6KER2Z6QdFQDQqFEjdO7cmUmZqgxFUZhDiXSKOZTsgYWtjun92nu342oWVSXmf+cRERHaDqQc2BGiqsRI3SCAOZSqFuZQsgcWtjp16tQpnDhxwjArWQDQsGFDdOnShUmZqgRFUdC1a1fDdIOAwo7Q8ePH8ffff2s9FCK7Yg4l0jfmULIHFrY6ZcSVLICrWVR1GK0bBPzz+4RfnMnZKYoCFxcX5lAinWIOJXtgYatTsiyja9euaNCggdZDKReTyYQTJ07g1KlTWg+FyG7++usvnDx50lDdIKCwI9S1a1cmZXJ65m4QcyiR/jCHkr2wsNUpo1x773bm1SzzGZ2JnFFsbKwhu0FAYUeISZmcndHOUWHGHEpVAXMo2QsLWx1KTU1FamqqIZNygwYN0LVrV26lIqdm3lHh7e2t9VDKTZIkdoTIqZm7QcyhRPrEHEr2wsJWh4x6bJCZyWTiahY5NaPuqAAKz7zq4uLCOUpOizmUSN+YQ8leWNjqkKIouPvuuw25kgUUrmadPHkSf/31l9ZDIbI5I++oAABvb292hMipybLMHEqkU8yhZE8sbHVGCGHIM8UVFRERwdUsclpG7wYB7AiRczNyNwhgDiXnxhxK9sTCVmdSU1Nx6tQpQydlb29v3H333Zz05JQURUG3bt3g5eWl9VAqTJIkddWcyJmkpqbir7/+MvTiMHMoOTPmULInFrY6Y17JCg8P13oolcJr8ZEzcoYdFQA7QuS8ZFlmDiXSKeZQsjcWtjojyzK6d+9u6JUsoHCbxl9//cXVLHIqzrCjAgC8vLzQrVs3JmVyOoqiMIcS6RRzKNkbC1sdEUIY9tp7twsPD4eLiwtXnMmpyLIMV1dXw3eDgH86QkIIrYdCZBPO0g0CmEPJOTGHkr2xsNWREydO4O+//zb8ShZQuJrVvXt3rmaRUzF3g+rXr6/1UCrNZDLh1KlT7AiR0zh58iRzKJGOMYeSvbGw1RFFUeDq6oqwsDCth2ITkiRBURSuZpFTcKYdFUBhR8jV1ZVfnMlpmHOoM3SDAOZQci7MoeQILGx1xHx8rTOsZAH/rGadPHlS66EQVZoz7agAgPr166N79+7c6khOQ5Zl9OjRA/Xq1dN6KDbBHErOhDmUHIGFrU6YV7KcZcIDQFhYGFxdXTnpySk4244KgMcIkfNwtm4QwBxKzoU5lByBha1OHD9+HGfOnHGqpGxezeI2DXIGztYNAgqT8unTp3HixAmth0JUKcePH8fp06eZQ4l0ijmUHIGFrU4405niijKZTDxGiAzPGXdUADxGiJyHsx1fa8YcSs6AOZQchYWtTiiKgp49e6Ju3bpaD8WmzKtZx48f13ooRBV27Ngxp9tRAQD16tVDjx49uNWRDE+WZeZQIp1iDiVHYWGrA8507b3bcTWLnIGiKHBzc3OqY4PM2BEio3PWbhDAHErOgTmUHIWFrQ78+eefOHfunFMm5bp166Jnz55MymRozrqjAijsCJ05c4YdITKsY8eO4ezZs065OMwcSs6AOZQchYWtDjjzShbAs8aRsTnzjgqg8Myrbm5u3EpFhiXLMnMokU4xh5IjsbDVAVmWERgYiDp16mg9FLswmUw4e/Ysjh07pvVQiMrNmXdUAOwIkfEpisIcSqRTzKHkSCxsNeaM1967HVezyMjM3aDQ0FCth2I37AiRUTl7NwhgDiVjYw4lR2Jhq7EjR47g/PnzTp2U69Spg8DAQK5mkSEpioJevXo5bTcIKOwInTt3Dn/++afWQyEql6NHj+L8+fNO2w0CmEPJ2JhDyZFY2GrM2Y+vNeNqFhlRVegGAUBoaCg7QmRIsiyjWrVqTt0NAphDyZiYQ8nRWNhqTJZl9OrVC7Vr19Z6KHZlMplw/vx5HD16VOuhEJXZkSNHcOHCBafuBgGFHaFevXqxI0SGY+4GMYcS6Q9zKDkaC1sNOfO1925nXs3ipCcjURQF1apVQ0hIiNZDsTtJkngtPjKUqnCOCjPmUDIi5lByNBa2Gjp8+DAuXrxYJZJy7dq10atXL27TIEOpKjsqgMKkfP78eRw5ckTroRCVyeHDh3HhwgXmUCKdYg4lR2Nhq6GqcmyQmclk4moWGUZV2lEBFHaEqlWrxo4QGYa5G8QcSqQ/zKGkBRa2GlIUBb1790atWrW0HopDSJKECxcu4PDhw1oPheiOUlJSqsyOCoAdITIeWZaZQ4l0ijmUtMDCViNV6dggM65mkZEoioLq1atXiWODzNgRIqOoat0ggDmUjIU5lLTAwlYjhw4dwqVLl6pUUq5VqxZ69+7NpEyGUNV2VACFHaGLFy+yI0S6l5KSgkuXLlWpxWHmUDIS5lDSAgtbjVTFlSyAZ40jY6iKOyoAICQkBNWrV+dWKtI9WZaZQ4l0ijmUOVQrLGw1Issy+vTpA09PT62H4lAmkwkXL15ESkqK1kMhKlFV3FEBsCNExqEoCnMokU4xhypaD6XKYmGrgYKCAsTGxla5lSyAq1lkDOZuUHBwsNZDcTh2hEjvCgoKqmQ3CGAOJWNgDmUO1QoLWw0cPHgQly9frpJJ2dPTE3369OFqFumaoigICgqqct0goLAjdOnSJRw6dEjroRBZdejQIVy+fLnKdYMA5lAyBuZQ5lCtsLDVgKIoqFGjRpVcyQL+Wc0qKCjQeihExVTlbhAABAcHsyNEuibLMmrUqIGgoCCth6IJ5lDSM+ZQ5lAtsbDVQFU9vtZMkiRcvnyZq1mkSwcPHsSVK1eqbFJmR4j0rqoeX2vGHEp6xhzKHKolFrYOZj6+tipuoTILDg5GjRo1OOlJl6r6jgqgcCtVbGwsO0KkO8yhzKGkb8yhzKFaYmHrYAcOHMDVq1er7EoW8M9qFrdpkB7JsoygoCDUrFlT66FoxtwROnjwoNZDIbJw4MCBKt0NAphDSd+YQ5lDtcTC1sFkWYa7u3uVXskCuJpF+sRuUCF2hEivFEVhDgVzKOkTc2gh5lDtsLB1MPOZ4jw8PLQeiqYkScKVK1dw4MABrYdCpEpOTq7yOyoAoGbNmggKCmJHiHTH3A1iDmUOJf1hDi3EHKodFrYOVJWvX3u74OBguLu7czWLdMXcDaqqZ1stih0h0ht2g/7BHEp6xBz6D+ZQbbCwdaCkpCSkpaUxKQPw8PDgahbpjizLCA4OrvLdIKCwI3T16lUkJydrPRQiAP/kUC4OM4eSPjGH/oM5VBssbB3IvJLVp08frYeiC5IkcTWLdKOgoABbt27ll+b/FxQUxI4Q6QpzqCXmUNIT5lBLzKHaYGHrQLIsIyQkhCtZ/89kMiEtLY2rWaQL3FFhycPDA8HBwUzKpBuKojCHFsEcSnrCHGqJOVQbLGwdJD8/nytZt+nTpw/c3d25lYp0QZZleHh4sBtUBDtCpBf5+fk8R8VtmENJT5hDi2MOdTwWtg6yf/9+pKenMykX4eHhgZCQEK5mkS6Yu0Hu7u5aD0U3zB2hpKQkrYdCVVxSUhLS09PZDSqCOZT0hDm0OOZQx2Nh6yCKonAlywrzalZ+fr7WQ6EqjN0g63r37g0PDw92hEhz5m5Q7969tR6KrjCHkh4wh1rHHOp4LGwdxHx8LVeyLEmShPT0dK5mkab279+Pa9euMSnfhscIkV6wG2QdcyjpAXOodcyhjsfC1gHMx9dyC1Vxffr04WoWaU6WZdSsWZPdICvM1+JjR4i0whxaMuZQ0gPm0JIxhzoWC1sH2LdvH65fv86VLCvc3d15jBBpjt2gkkmShGvXrmH//v1aD4WqqH379rEbVALmUNID5tCSMYc6FgtbB+BKVulMJhO2bt3K1SzSBLtBpevduzdq1qzJL86kGUVRmENLwRxKWmIOLR1zqGOxsHUARVEQGhqKGjVqaD0UXTKvZu3bt0/roVAV9Mcff3BHRSnMHSFudSStyLLMHFoK5lDSEnNo6ZhDHYuFrZ3l5eXx+rV3wNUs0pKiKPD09ESvXr20HopusSNEWsnLy8O2bdvYDSoFcyhpiTn0zphDHYeFrZ398ccfuHHjBpNyKWrUqIHQ0FCuZpEm2A26M0mScP36dfzxxx9aD4WqGHaD7ow5lLTEHHpnzKGOw8LWzswrWYGBgVoPRdckScK2bduQl5en9VCoCjF3g/iluXS9evWCp6cnO0LkcMyhZcMcSlpgDi0b5lDHYWFrZ7IsIywsjCtZd2AymXD9+nUeI0QOxR0VZWPuCDEpk6MpisIcWgbMoaQF5tCyYQ51HBa2dsSVrLILDAyEp6cnt1KRQ8myjFq1arEbVAaSJGHr1q3sCJHDMIeWHXMoaYE5tOyYQx2Dha0dJSQkICMjg0m5DGrUqIGwsDCuZpFDmbtB1atX13ooumcymXDjxg0eI0QOk5iYyG5QGTGHkhaYQ8uOOdQxWNjakaIoXMkqBx4jRI6Um5vLblA5sCNEjmbuBvXs2VProRgCcyg5EnNo+TCHOgYLWzsyH1/LlayykSQJN27cQGJiotZDoSogMTGROyrKoXr16uwIkUOxG1Q+zKHkSMyh5cMc6hgsbO0kNzcXcXFx3EJVDoGBgahVqxZXs8ghZFlG7dq12Q0qB5PJhG3btiE3N1froZCTM3eDmEPLjjmUHIk5tPyYQ+2Pha2dJCQk4ObNm1zJKgeuZpEjsRtUfpIkISMjgx0hsjvm0PJjDiVHYg4tP+ZQ+2NhaydcyaoYk8mEuLg4rmaRXXFHRcX07NkTtWvX5hdnsjtFUZhDK4A5lByBObRimEPtj4WtnSiKgvDwcFSrVk3roRiKeTUrISFB66GQE9u7dy+7QRVg7ghxqyPZmyzLzKEVwBxKjsAcWjHMofbHwtYOcnJyEBcXxwlfAT169OBqFtmdoiioU6cOevToofVQDEeSJHaEyK7M3SDm0PJjDiVHYA6tOOZQ+2Jhawd79+5FZmYmt2hUQPXq1REeHs7VLLIrdoMqzmQy4ebNm9i7d6/WQyEntWfPHubQCmIOJUdgDq045lD7YmFrB+aVrO7du2s9FEPiahbZU05ODrZv385uUAX16NEDderUYUeI7IY5tHKYQ8memEMrhznUvljY2oEsy4iIiOBKVgWZTCZkZmZiz549Wg+FnBC7QZVTrVo1doTIrphDK4c5lOyJObRymEPti4WtjXElq/K6d+/O1SyyG0VRULduXXTr1k3roRiWJEnYvn07cnJytB4KORnm0MpjDiV7Yg6tPOZQ+2Fha2O7d+/GrVu3mJQroVq1aoiIiGBSJrtQFIXdoEoyd4R4jBDZ2p49e3Dr1i12gyqBOZTsiTm08phD7YeFrY2ZV7J4bFDlcDWL7CE7O5vdIBvo1q0b6taty61UZHOyLLMbZAPMoWQPzKG2wRxqPyxsbcx8bJCbm5vWQzE0SZJ4jBDZnLkbxKRcOeZjhNgRIlszd4OYQyuHOZTsgTnUNphD7YeFrQ1lZ2djx44d3EJlA927d+dqFtmcLMuoV68eu0E2YDKZsH37dmRnZ2s9FHIS5m4Qc2jlMYeSPTCH2g5zqH2wsLWh3bt3IysriytZNuDm5sZjhMjm2A2yHUmScOvWLXaEyGaYQ22HOZTsgTnUdphD7YOFrQ3Jsoz69evj7rvv1nooToGrWWRL3FFhW926dUO9evXYESKbYQ61LeZQsiXmUNtiDrUPFrY2xJUs25IkCVlZWdi9e7fWQyEnsGvXLnaDbIgdIbI15lDbYg4lW2IOtS3mUPtgYWsjWVlZ2LFjBye8Dd19992oX78+Jz3ZhKIoqF+/Prp27ar1UJyGJEnYsWMHO0JUaVlZWdi5cydzqA0xh5ItMYfaHnOo7bGwtZFdu3YhOzubWzRsyLyaxW0aZAuyLCMyMpLdIBsymUzIysrCrl27tB4KGZy5G8QcajvMoWRLzKG2xxxqeyxsbURRFHh5eXEly8YkScLOnTuRlZWl9VDIwNgNso+uXbuyI0Q2wRxqH8yhZAvMofbBHGp7LGxtxLyS5erKH6ktcTWLbCE+Pp47KuzAzc0NkZGR7AhRpTGH2gdzKNkCc6h9MIfaHjOIDWRlZSE+Pp4rWXbQtWtXeHl5cTWLKkVRFHh7e6NLly5aD8XpsCNElcUcaj/MoWQLzKH2wxxqWyxsbWDnzp3Izs5mUrYDV1dXREZGMilTpSiKwm6QnZhMJmRnZ7MjRBXGbpD9MIeSLTCH2g9zqG3xX6gNcCXLvriaRZVx69YtHhtkR126dIGXlxe3UlGFybIMb29vdO7cWeuhOCXmUKoM5lD7Yg61LRa2NsBjg+xLkiRkZ2cjPj5e66GQAcXHxyMnJ4dJ2U7YEaLKYjfIvphDqTKYQ+2LOdS2mEUqKTMzE7t27eIWKjvq0qULvL29uZpFFSLLMho0aMBukB2ZTCbs3LkTt27d0nooZDC3bt1CfHw8c6gdMYdSZTCH2h9zqO2wsK0krmTZH1ezqDLYDbI/SZKQk5PDjhCV286dO5lD7Yw5lCqDOdT+mENth/9KK0mWZTRs2BCdOnXSeihOzWQyIT4+nqtZVC6ZmZnsBjlA586d0aBBA3aEqNyYQx2DOZQqgjnUMZhDbYeFbSVxJcsxzKtZO3fu1HooZCA7d+5Ebm4uu0F2xo4QVRRzqGMwh1JFMIc6BnOo7TCTVIL5+FpOePvr1KkTGjRowElP5aIoCho2bIiOHTtqPRSnJ0kSdu3ahczMTK2HQgbBHOo4zKFUEcyhjsMcahssbCthx44dyM3N5RYNB3B1dYUkSdymQeUiyzIkSWI3yAFMJhM7QlQuzKGOwxxKFcEc6jjMobbBf6mVoCgKGjVqxJUsB+FqFpXHzZs3sXv3bnaDHKRjx45o2LAhO0JUZsyhjsUcSuXBHOpYzKG2wcK2EswrWS4uLloPpUowmUzIzc3Fjh07tB4KGQC7QY7FjhCVF3OoYzGHUnkwhzoWc6htsLCtIK5kOR5Xs6g8zN2gDh06aD2UKkOSJOzevRs3b97Ueiikc8yhjsccSuXBHOp4zKGVx8K2grZv3468vDwmZQdycXHhahaVGbtBjidJEjtCVCbMoY7HHErlwRzqeMyhlcfCtoIURUHjxo25kuVgJpOJq1l0RxkZGdizZw+3UDlYx44d0ahRI3aE6I6YQ7XBHEplwRyqDebQymNhW0FcydKGJEnIy8vjahaVaseOHewGacDcEWJSpjtRFIU5VAPMoVQWzKHaYA6tPBa2FcCVLO106NABjRs35lYqKpUsy2jSpAnat2+v9VCqHHNHKCMjQ+uhkE4xh2qHOZTKgjlUO8yhlcPCtgK2b9+O/Px8rmRpgKtZVBbsBmmHHSG6Ex5fqx3mUCoL5lDtMIdWDgvbCpBlGU2bNkW7du20HkqVZDKZsGfPHq5mkVU3btxgN0hD7du3R5MmTdgRohIxh2qLOZRKwxyqLebQymFhWwFcydKWeTVr+/btWg+FdIg7KrTFjhDdCXOotphDqTTModpiDq0cFrbldOPGDezdu5cTXkPt2rVD06ZNuZpFVpm7QQEBAVoPpcqSJAl79uzBjRs3tB4K6QxzqPaYQ6k0zKHaYw6tOBa25RQXF4f8/Hxu0dAQV7OoNIqiwGQysRukIZPJhPz8fHaEqBjmUO0xh1JpmEO1xxxacSxsy0lRFDRr1gxt27bVeihVmiRJ2Lt3L1ezyML169eRkJDAbpDGAgIC0LRpU35xpmKYQ/WBOZSsYQ7VB+bQimNhW06yLHMlSwfMq1lxcXFaD4V0hN0gfXBxcYHJZOJWRyqGOVQfmEPJGuZQfWAOrTgWtuXAlSz9aNu2LZo1a8bVLLKgKAqaN28Of39/rYdS5UmShISEBFy/fl3roZBOMIfqB3MoWcMcqh/MoRXDwrYctm3bhoKCAiZlHTAfI8TVLCpKlmWebVUnJEliR4gsMIfqB3MoWcMcqh/MoRXDwrYcFEXBXXfdxZUsnTCZTFzNItW1a9eQmJjILVQ60bZtWzRv3pwdIVIxh+oLcygVxRyqL8yhFcPCthy4kqUvkiShoKAA27Zt03oopAPsBukLO0J0O+ZQfWEOpaKYQ/WFObRiWNiWUXp6Ov744w+uZOmIv78/7rrrLq5mEYDCblCLFi3g5+en9VDo/5lMJiQmJuLatWtaD4U0xhyqP8yhVBRzqP4wh5YfC9syiouL40qWzvBafFSUoijsBumMuSPEY4SIOVR/mEOpKOZQ/WEOLT8Wtnfw119/Yd++fZBlGS1atECbNm20HhIVYV7Nunz5MjZs2KD1cEgDGzZswKVLl9gN0iE/Pz+0aNECsixj3759OHXqlNZDIgcrmkNbtmzJHKozzKHEHKpfzKHlx8L2DhYtWoQRI0ZAURRERkbi888/55YAndiwYQOaNGmCgoICvPnmmxg4cCCys7O1HhY5UHZ2NgYOHIgFCxagoKAATZo04Zcznbh27Ro+//xzREREQFEUDB8+HIsWLdJ6WORgRXNoREQEc6iOMIcSc6h+MYdWDAvbO+jSpQuOHTuGxMREnD17FtOmTcOFCxe0HhYBWLlyJcaPH48mTZrg999/R7t27eDu7q71sMiB3N3dERAQgN9//x1NmzbFuHHjsHLlSq2HRQAuXLiAadOm4dy5c0hMTMTx48fRpUsXrYdFDsYcql/MocQcql/MoRXDwvYOgoKC1D/LsoxPP/0UAQEBGo6IzD744AM0bdoUmZmZOHz4sEWsqOoICgrC4cOHkZGRgaZNm+KDDz7QekgEICAgAJ988glkWYYQAgA4R6sg5lD9Yg4lgDlUr5hDK4aF7R34+PjA09MTAPDcc89h8uTJGo+IzOrXr49ffvkFQOF2mrvvvlvjEZEW7r77bmRnZ8PV1RW//PIL6tevr/WQ6P9NmTIFM2fOBADUqlULrVq10nhE5GjMofrFHEoAc6ieMYeWn4swLwNQicLDw3Hr1i3s3r0brq5cC9CbdevWYeTIkdi2bRt69uyp9XDIwRISEhAeHo7vv/8eAwcO1Ho4dJuCggL06tULnp6evF5mFcUcqm/MoVUbc6i+MYeWDwtbIiIiIiIiMjQunRIREREREZGhsbAlIiIiIiIiQ6tmqxc6deoULl++bKuXo0pq2LBhqQeZM17O5dy5cwCAZs2aaTwSsgXG0/lkZ2fzUipOpGiOZT41LnMcGUPnwhzqnO5U2wA2KmxPnTqFDh06IDMz0xYvRzbg6emJlJQUq/8AGC/n4+rqioKCAq2HQTbCeDofNzc35Ofnaz0MshFzjgXAfGpgnp6e2Lx5M2JiYhhDJ8Ic6pxKq23MbFLYXr58GZmZmVixYgU6dOhgi5ekSkhJScFDDz2Ey5cvWw0+4+VczPFmPJ0D4+l81q9fj1dffZUxdRJFcywA5lODMsfxxIkTjKETYQ51TneqbcxsthUZKFy17NGjhy1fkuyI8XIujKdzYTydR9HOHmPqnBhb42MMnQvjWTXx5FFERERERERkaFWisJ0zZw5WrFih9TDKRAiBZ599FuHh4YiJicHp06eLPSY9PR1DhgxBeHg4JkyYgJycHA1Gaj9GitfRo0fRo0cP1K5dG3Fxcertc+bMQZ8+fRAaGoonn3wS1i4XnZSUhLCwMISEhODdd98FUHj8syRJ6n/Vq1dHWloadu7ciZCQEERGRiIqKgonTpxw2GesLGeIZ1nm3LBhwxAZGYnAwED8+9//trjvypUr8PLyUn8Oqamp8PLyUuP8888/2/eD2VBVjueFCxcQEhICSZLQp08f/P777xbP2bJlC1xcXKz+3tYrZ4jn0aNHIUkSTCYTnnvuOavPbd26tTrf5s6dC6Aw306ePBkRERG45557cObMGQDA3Llz1cf6+vrif/7nf+z/4ezESPEFgG+++QbR0dEwmUx4//33i91fUqx//vln9OnTB+Hh4fjmm28AALt371bjGBQUhAYNGjjsc9iSkWJY0hw1e+211+Dv72/1uZIkITg4GJIkYdq0aQAK5+iMGTMQHByMXr16qT+HRYsWqbFt3749hg0bZr8PZWNGiqdZSbltyZIlqF69utXnTJkyBUFBQQgKCsKCBQvU2wcNGoTQ0FD06dMHX375JYDCnBwdHY2wsDAEBQVhw4YNFR6roQtbR52Io+j7CCGsFimlPac8fvvtN1y+fBnbtm3D888/j1mzZhV7zFtvvYUhQ4Zg27ZtaN68Ob766qsKvZejOWO8WrRogd9//x3Dhw+3uH3MmDHYtWsXtm/fjvPnz2PLli3Fnjt9+nR88cUXiIuLw5o1a3D8+HG0atUKiqJAURTMnz8fffv2hZeXF3x8fPDbb78hNjYWM2fOxOzZsys0XluqSvEsy5xbuXIlYmNjER8fj08++QQ3btxQ75s3bx7CwsIsHt+zZ0811oMHD67QeG2J8bRkLZ4NGzbEtm3boCgKVq5ciRdffFF9fEFBAd555x0EBgZWaKy2VpXi+fzzz2PBggWQZRlpaWmQZbnYc93c3NT59tprrwEA1qxZAzc3N2zduhWvvPIKXn75ZQCFX77Njw0ICMCDDz5YofHakzPGNyUlBWvXrsVvv/0GWZbx1FNPFXuMtVgXFBTgueeew+bNm7Flyxa89957uHHjBnr37q3G8cknn9RdHJ0xhiXNUQA4c+YM/vzzz1Kf//3330NRFHzyyScAgIMHD+LgwYPYuXOnxdydMmWKGtuIiAhdxNYZ4wmUnNsyMzPx008/lXi868yZMxEfH48dO3ao33EB4L333sP27dsRGxuLf/3rX8jKyoK7uzu+/PJLxMXFYd26dXj66acrPF67FbapqakIDQ2FyWSCJElIS0vDhQsXEB0djX79+mHatGmIiYkBAEyYMEFd2VEUBZMmTQIAvP/++4iKikJgYCBeeeUV9bV9fHwwffp09OvXD9euXcPIkSMRFRUFk8mEo0ePAgBWrVqFbt26YfDgwUhISChxnLm5uZg8eTKioqIQFhaGnTt3qmN6/PHHcd9992Hjxo3w9/fHrFmzEB0djdOnT2PUqFGIjIxEaGio+vq3P6ciZFnG0KFDAQB9+/bF7t27S33M/fffbzWJlxfjVbF4eXp6wsvLq9jtAQEB6p/d3d3h5uZmcX92djauX7+Otm3bwtXVFYMGDUJsbKzFY5YtW4Zx48YBAJo3b45atWqV+Hq3YzxtG8+yzLkaNWoAKPxl36pVK3h6egIAjh07hitXrqBnz54Wj9+/fz/Cw8Px0EMP4dKlS6WOi/HURzzd3NzUuZeeno6uXbuqj1+xYgUGDx6sztPSMJ62jefRo0fVL12BgYFW4ymEgMlkQv/+/ZGYmFim5509exanT59G7969yzVOxrdi8f3+++9Rr1493HPPPRg4cCCOHDlS7DHWYnb58mU0atQIderUQfXq1dGmTRvs2bPH4nlF82lZMIa2naNAYaey6M/hdi4uLhg1ahRMJhM2b94MoPC7T40aNZCbm4sbN27A29vb4jlZWVnYtGnTHReHGc+KxRMoObe98847eOKJJ+Di4mL1eebvwa6urqhWrZqaO82316hRA66urnBxcUHNmjXRokULAEDNmjVLfM0yETaQkJAgAIiEhAT1tiVLlojZs2erfy8oKBBPPfWUWLFihXp/dHS0EEKIhx9+WGzbtk0IIYQsy+LRRx8VQgiRkZGhPjcoKEikpqYKIYSoVq2aOHnypBBCiBdeeEGsXLlSCCHEgQMHxJAhQ0R+fr4ICAgQ6enpIj8/X0RGRorly5dbHfunn34q3nzzTSGEEBcvXhRBQUHqmObNm6c+zsfHR8TFxQkhhPjPf/6jfrbDhw+LPn36WH1OUY8//riIjIy0+G/gwIHFHjd58mQhy7L697Zt2xZ7TEBAgCgoKBBCCHH06FExYMAAi/utxeNO9zNelsoaL7OiP5OiZFkWkiSJ/Px8i9vPnDkjIiMj1b8vWrRIvPXWW+rfs7OzRatWrURmZqbF8zIyMkRwcLDYt2+fehvjaf943mnOmQ0ePFg0atRIvPbaa+pto0ePFseOHROzZ89Wfw5ZWVni+vXrQojCWIwfP159POOp73ieOHFChIaGioYNG4q1a9cKIYTIzMwU0dHRIjc3V0RGRoq///7b4nVWrFhhEVPG01Jl4zlixAixdu1aUVBQIIYOHSqmT59e7DmXLl0SQgiRnJwsOnToIIQQ4pdffhHDhw8XBQUFYtWqVaJWrVoWz3nrrbfEv/71r2KvVXSOcr7aLr5TpkwR999/v8jPzxe7d++2yJFm1mJt/synT58W6enpolWrVuL7779Xn3Pu3DnRrl27Yq9ljt3t81MIxvB2lZ2j+/fvF5MmTRJCCOHn52f1OeY5evr0adGuXTuRnp4uCgoKxOOPPy58fX1Fo0aNxE8//WTxnO+++079eZtxTtouniXltnPnzonBgwcLIUqOp9ny5cvF6NGji90+b9488dJLLxW7fdKkSWLhwoXFbr9TbWNm07MiFzVy5EjMnz8fY8eOhY+PD+bMmYMjR47giSeeAACEhITg66+/BgCLylwUaan/+OOPWLx4MVxcXHDy5EmcPn0aPj4+aNGiBXx9fQEAycnJiI2NxWeffaa+1qVLl9C4cWPUq1cPABAUFFTiOJOTk7Fjxw78+uuvAApX4c2Kbh10c3NDSEgIAODw4cPqfv527drhypUrVp9TlHlbxZ00aNAAaWlp6s+iWrXiIfL29kZ6ejq8vLyQnp5uk+NGGC9LZY1XaRITE/HSSy9h3bp1cHW13BxhjqHZ7XFcu3YtoqKiULNmTfW27OxsDBs2DC+99BLuvvvuUt+b8bRU2XiWdc6tWbMGN2/eVLdGmR/r5+dn8Th3d3e4u7sDAMaOHYv33nuv1PdnPC1pFc+OHTuidevWiIuLw4kTJxAVFYVBgwbhP//5D6ZOnWr197U1jKelysbz3XffxYwZM/D++++jTZs2aN68ebHHNGzYEADQuXNn1K9fH5cuXcKAAQOwY8cOSJKEXr16oX379hbPWbFiBdasWVPu8TC+lsoaX29vb3Tv3h2urq7o1auXesxzUdZi7erqioULF+Khhx5CnTp10K1bN4t/A1999RVGjx5dpjGYMYaWKjtHX3vtNXz00UelPsY8R++66y706NEDR48exdWrV3HmzBkcO3YM165dQ1hYGAYMGKDmz2XLlmHmzJl3fH/G01JZ41lSbrtT991sw4YNWLZsWbHziCxevBgHDx4sdqzxq6++Cm9vb0yZMqVM47PGboWtq6sr5s+fDwCYOHEiNm7ciICAAOzatQt+fn6Ij49XH+vt7Y1Tp04BgMX2kVdffRWHDx+Gu7s7QkND1X9gRbdhdurUCcHBweq2spycHLi5ueHChQu4fv066tSpg927d6Nz585Wx9mpUyf4+/vjmWeeUZ9vVvR9XFxc1H/s7du3x7Zt2xATE4MjR45YfCkqaYvotGnTcOjQIYvbateujXXr1lncJkkSvvnmGwwdOhRbtmyxeryW+WQzDz/8MH7++WdIkmT1PcuD8bJU1niVJCUlBVOmTMHq1autfmn28PBAnTp1cOLECbRu3Rrr16/H559/rt6/fPlyPPnkk+rf8/LyMGrUKIwePRr33XffHd+f8bRU2Xjeac4VFBQgPz8f1atXR82aNdX/Nm/ejKSkJNxzzz04duwYatWqBT8/P3Ts2FFNcrIsW2xdt4bxtKRVPLOzs9UvVHXr1kXt2rUBFB4HFhsbi8WLFyMpKQnjxo3DunXrStyWzHhaqmw8W7ZsiTVr1kAIgfHjx6uf1yw7OxtCCHh4eODcuXO4dOmSOq558+YBADZu3KhuPweAffv2oV69euoX1vJgfC2VNb7R0dHqiZ9OnDhRbNspUHKszScSunHjBoYNG4ZevXqpz1mxYgV++OEHq2MrCWNoqbJz9Pjx4+qW3nPnzmH69On4+OOP1fuFELhx4wbq1q2LjIwM7N+/H76+vrh69Sq8vb3h5uaGOnXqIDc3Vz1e9NKlS0hJSUFERMQd35/xtFTWeJaU244dO4ZXX30VQGE8hw8fXmyObd26FfPmzcP69evh4eGh3v7tt99i1apVWL16tUXT5+2338bZs2exZMkSq2MuK7sVtuvWrcOHH34INzc3uLu7IywsDIGBgRgzZgy++OILi6BOmjQJY8aMwddff43WrVurtz/wwAMIDQ1F+/bt1S8Qt5s1axamTp2KDz/8EADQv39/vPDCC3jzzTcRERGBli1bWv3laDZ58mTMmDEDJpMJANC9e/c7dk8mT56MCRMmICIiAnl5eep7l6asqyP9+vXDhg0bEB4eDnd3d3zxxRcAgF9//RWXLl3CuHHj8Pzzz+Phhx/GkiVL4Ovrq/7jqgzGy1JZ45WWloYRI0bg0KFDOHjwIPr374958+bh8ccfx/Xr1/HQQw8BAJ599lkMHjwYCxYswMCBA9GlSxd88MEHGD9+PAoKCjB06FD1TIFXrlxBUlKSxZftFStW4Pfff0daWhq++OILdOzYsdQxMp6WKhvPkuacOZ6+vr7qgkN2djZGjRqF1q1b48knn1QXKObMmQN/f38EBwdj9erVmDt3LurUqQN3d3csWrSo1HExnpa0imdcXBxefvlluLm5ITc3Vz1ra9FVZ0mSsHz58lKPtWU8LVU2nl9//bW6MDhhwgR06NABAPD0009j1qxZyMrKwpAhQ1CrVi3k5eXh008/haurK9LS0jB06FC4ubnBx8fHoqO0fPly9fd3eTG+lsoa3+joaGzatAmSJCEnJ0d97aLff0qK9fPPP489e/agWrVqWLBggXqm1uTkZHh6ehbbNXMnjKGlys7R5ORk9TH+/v5qUWv+ndu+fXuYTCbUrFkTOTk5eOWVV9CoUSPExMRg5cqVCA0NRU5ODp544gn1/BXffPMNRo4cWabjMRlPS2WNZ0m5zXwMNFAYT3NRu3TpUtx1113o27cvxo8fj7p162LIkCEACk/a2K1bN4wbNw7dunVD3759ARR23fPz8/HCCy8gNDRU/e67adMmi8XGMit1o3IZlXXfc1EnT55U97OTbVXkGNs7Ybz0i/F0Loyn87F2DF9pGE99u9MxtnfC+OpDacfY3gljqF+ck85J82Ns9Wj8+PHq9gKgcLvBTz/9pOGIqDSMl3NhPJ0L4+lcGE/nxvgaH2PoXBhP+9CssPX19bVoZTvCsmXLHPp+zoTxci6Mp3NhPJ0L4+ncGF/jYwydC+PpPOx2HVsjMR/baG8LFy5E7969ERERgdGjRyM7O9sh7+vMHBW7uLg4dOnSBR4eHjh9+rR6+61btzB16lTExMRAkiT1unuSJCE4OBiSJGHatGkOGaOzcVRsAeDf//43YmJiYDKZ8O233wIoPLmC+YQkTZs2LdNxK1QyR8Vz6dKlaN26tRo784r433//jZiYGISHh5fpLJp0Z46cowCwZMkS9dhJAHjjjTcQERGB0NBQjB8/Hrm5uQ4djzPTOrZUeVp/t/3hhx/QoUMHixMHkW1oHVs9Y2HrQNHR0YiPj8fWrVvRsmXLYqe5Jv3q0qULdu7cWew07XPnzsXgwYOxefNmKIqCdu3aqfd9//33UBTFJpcOIvvZuHEjzp8/j82bN0OWZTz44IMACk+uoCgKFEWBt7c3hg8frvFIqaweffRRNXatWrUCALzwwgt4+eWXsW3bNpw9exayLGs8SiqPzMxM/PTTT2o8AeC5557D1q1bsX37dgCFJxsh47EWWzKOkr7bSpKEP/74Ay1atNB4hFRRRqxbdF3YpqamIjQ0FCaTCZIkIS0tDVu3boXJZEJ4eDgGDx6MW7duASicQM888wz69+8PSZLw9ddfo3///ujWrRuOHj2qPmb69Ono27cvoqOjcfHiRYv3y83NxeTJkxEVFYWwsDDs3LkTQOHlAHr37o2oqKg7np2sNP7+/uqprd3d3Us8DbczcLbY1atXz+pZ8DZt2gRZliFJEp599lnk5eUBKDwV+6hRo2AymRy+vcXenC223377LfLz8xETE4MRI0bg/PnzFvfHx8ejZcuWaNasWYXfQ8+cLZ5A4RavsLAwzJo1CwUFBQAKrysdFRUFALj//vudurB1xpi+8847eOKJJyzOgGo+Y2ZBQQHy8vIc3mXUQlWJrTNzthiW9N22YcOGVa5bW1Viq2uOPFNVeS1ZskTMnj1b/XtBQYHIyMhQ//7888+LpUuXCiGEiIyMFKtWrRJCCPHoo4+Kp59+WgghxPLly8ULL7ygPubLL79UX3vmzJlCCCH8/PyEEEJ8+umn4s033xRCCHHx4kURFBQkhBCiffv26vvm5+cXG+fQoUNFZGSkxX+PPvpoiZ/r0KFDomfPnhafxZbscVbk8nLW2EVGRoq///5b/XuNGjXETz/9JIQQYsaMGWLJkiVCCCEuXbokhBDi9OnTol27diI9Pb30H1glOCKeRTlbbPv16yeefPJJIYQQ33//vRg3bpzF/dOmTRPLly8v64+n0hjPysXz6tWrIi8vT+Tl5YkJEyaI//73v0IIIdq2bas+ZtOmTWLatGnl+TFVSkXOuloZzhbTc+fOicGDB1u8p9lrr70m/Pz8xL333itu3rxZ1h9RpVT2rMiVUZVia2+VOStyZThbDM1K+m6rVVwdFc+iqlpsHckpzoo8cuRIzJ8/H2PHjoWPjw/mzJmDgwcP4pVXXkF2djYuXLiAunXrqo/v2bMnAKBFixbqNctatGiB2NhY9TEhISHq/1etWmXxfsnJydixYwd+/fVXAEB6ejoA4KOPPsL06dORl5eHqVOnIiwszOJ55TmLWWpqKh5++GF89913pV7n0OicMXbWeHt749577wUADBw4EOvXrwdQuFIJAHfddRd69OiBo0ePWlww3sicLbZFYzho0CDMnTtXvS8nJwe//PIL3nrrrTK9lhE5Wzy9vLzUP48ePRpr1qzBI488YnEh+PT0dIuL2DsbZ4vpnDlz8Morr1i97/XXX8ecOXMwffp0LF261OnPaVCVYuusnC2GQNX5bnsnjK32dF3Yurq6Yv78+QCAiRMnYuPGjVi8eDFef/11BAcH4/nnn4cQQn180W0sRf9c9DHx8fHw9/dHfHy8xfGQANCpUyf4+/vjmWeeAVD4pRYAgoODER0djVOnTmHo0KFISEiweN4DDzyAq1evWtzm7++PxYsXW9x2/vx5jBgxAkuWLEGbNm3K/fMwEmeLXUmio6Oxd+9ehIWFYdeuXQgICIAQAjdu3EDdunWRkZGB/fv3w9fXt0yvZwTOFltzDO+55x41hmbr169HRESEIX6ZV5SzxTM9PR3169cHAGzZskV9/+7duyM2NhaRkZH4+eef8cgjj5T9h2QwzhbTY8eO4dVXXwUAnDt3DsOHD8cPP/yArKwseHh4wMXFBfXq1YOnp2f5flAGVFVi68ycLYZV6bvtnTC22tN1Ybtu3Tp8+OGHcHNzg7u7O8LCwpCRkYFHH30U7du3R926dS1WPsoiMTERX375JfLz87Fy5UqL+yZPnowZM2bAZDIBKPwi9N5772Ho0KHIyspCVlYWpk+fXuw1y7ry8eKLL+LChQt48sknAQBjxozBlClTyjV+o3C22KWkpOCJJ57A/v37MXr0aDz44IOYMWMGFixYgEmTJiErKwuNGzfGsmXLkJeXB5PJhJo1ayInJwevvPIKGjVqVK7PqmfOFtvx48dj6tSpMJlMEEJY/GJfvnw5HnvssXJ9FqNxtni+/fbb2Lx5M6pVq4a2bduqHfgFCxZg4sSJyMnJQWBgoPr+zsjZYlr0PAX+/v5q4TNt2jScOHEC+fn5CAgIsNht4ayqSmydmbPFsKTvtoqiYN68eTh79ixiYmLw2GOPYcSIEeX6XEZTVWKra47c96y124+PdFZ6OMbW1qpK7CrCiPEsirG1xHg6H0cfw2drjKklLY+xtbWqHFutjrG1taocQ2uMPieLYmz/Uda46vqsyERERERERER3ouutyLamKIrWQ6AKYuycF2PrXBhP58OYOi/G1vgYQ+fF2Jaf03RsU1NTERMT47D3mzNnDjp06ABJkiBJknrAdlJSEsLCwhASEoJ3333X6nNXrFiB4OBgBAcHO/W1FMtCi7j16dMHoaGhePLJJ9UD9KdMmYKgoCAEBQVhwYIFVp/7119/4f7770dUVJR6Fl0AqFmzpvrvYNGiRQCAX3/9FaGhoZAkCVFRUfj777/t/+F0wNHx/OGHH9ChQ4di18q7cuUKxowZg+joaEiShOvXr1vcL4TAjBkzEBwcjF69eqkXHV+0aJEay/bt22PYsGEASv53UxXoJaaDBg1CaGgo+vTpgy+//NLqc0v73XrkyBFUr14dcXFxAIA1a9agT58+iIyMxMCBA3HlyhX7fCCdcXQ833jjDURERCA0NBTjx49Hbm4ugLLFEyicy15eXuocBQpPChYTEwOTyYSXXnoJQOEXwGbNmqnzd/fu3fb9YDqhl/lpFhERgUmTJhW7/cKFCwgJCYEkSejTpw9+//13ACXPw6VLl6J169ZqPE+dOmW/D6Ujjo6n2WuvvWZxHehbt25h6tSpiImJgSRJOHLkiMXj09PTER0djbCwMAQFBWHDhg0W998+b3NycjBy5EiEh4ejd+/e+O233+z/oXRIL995N2zYgF69eiE8PByjR49Wfy8XZe27rSF+zzpy37M9nTx5UkRHRzvs/WbPnm312pZhYWHi6NGjIj8/X4SHh4tjx45Z3J+WlibuvvtucevWLXHp0iVx9913W73GVGUY6RhbR8ftyJEj6p9HjBghNm/ebHF7fn6+CAoKKhY3IYQYMGCAOH36dLHbrV2jLTs7W/1z0WuP2UNVjuelS5fErVu3isVg3LhxYt++fSU+Lzk5WUiSJIQQIiMjQ7Ru3brYYyZPniy+/fZbIUTJ/27sQU/xFEI/MTXHwHzfrVu3LO6/0+/WUaNGiZiYGLFt2zYhROHnysnJEUII8fHHH4tXXnnFbp9JT8fwOTqeRX8Xjhs3Tqxbt04Iced4mj399NNi0KBBar69fPmyGDBggMjKyrJ4nCzLpV6H0Zb0dIytXuanEEL89NNP4r777rMaB/O1pYUQ4vjx4yIwMFAIUfI8/OKLL8S//vUve30MIYQ+j7F1dDyFEOL06dNi1KhRFjF98cUXxS+//FLiczIzM9VjPy9duiQCAgIs7r993q5du1ZMmDBBCCHEqVOnRI8ePWz9MVRaz8nS6OU7b8+ePUVqaqoQovAauj///HOx51qb4478PXs7pzjGdubMmfjxxx8BAHl5eejatStyc3Px8ssvIyoqCj169MCnn35a7HkTJkxQV+UVRVFXDw8cOICYmBhERUVhxIgRyMzMrNT43nrrLYSFheHf//43ACA7OxvXr19H27Zt4erqikGDBllciwoAdu3ahcjISHh4eKBhw4Zo3rw5UlNTKzUOvdFz3IpeysXd3R1ubm4Wt7u6uqJatWrq7WanTp3CzZs38T//8z+IjIzEkiVL1PvOnz+PyMhI3H///Thx4gQAoEaNGur96enp6Nq1a4XHrDU9x7Nhw4bFOgf5+flISkrCRx99hMjISLzxxhvFnte8eXPUqFEDubm5uHHjBry9vS3uz8rKwqZNmzB48GAAJf+7MSqjxRT4JwY1atSAq6urxaURgNJ/t27duhW+vr6466671Mf7+vqievXqAIwfUz3H0/y7sKCgAHl5eWpX6E7xBAovBXPlyhX1Wo8A8Msvv6BRo0a4//77ERMTg/j4ePW+TZs2ISwsDNOmTat0fteSnuNZ0vzMy8vDp59+avUMrADg5uamzrGiObG0ebhs2TKEhYVh1qxZKCgoqPCYtabneALWryW8adMmyLIMSZLw7LPPIi8vz+L+mjVrokWLFuqfi85fa/PWz88P2dnZEEIgLS0NjRs3rtSY9UTP8S3pu0unTp2Qnp4OIQTS09OtXrnD2ndbQP+/Z3Vd2E6YMEHdorRx40ZERUWhevXqmDVrFrZs2YKdO3fi3//+t9UWujXTpk3Df//7X2zZssWitW6Wk5OjtteL/mft4uHmS79s3rwZv/76K2RZVrdemHl5eRXb3laWxxidnuNmpigKTp8+jYiICIvbV6xYgZYtWxa77uyZM2eQkJCAt956Cxs3bsTnn3+OP//8E0Dh1pLY2Fg88cQTmDhxovqcVatWITAwEJ9++imCg4PL9Fn1yAjxLOrixYtISkrC1KlTIcsydu/ejS1btlg8xsvLC35+fggICEDXrl0xa9Ysi/vXrl2LmJiYYl/gSvp3YzRGi2lRb775JoYPHw53d3eL20v63SqEwPz58/HCCy9Yfb3z58/jo48+0v8lDEqh93jOnj0bAQEBSE9PR8uWLS3uKymeQOH2yNmzZ1vcdubMGaSkpGDVqlVYsmSJ+ju3Z8+eOHr0KOLi4tCwYUP87//+b5k+qx7pPZ7WfPbZZ3jooYesxtHs5MmTCAsLQ//+/TF06FCL+26fh0OGDEFKSgpiY2Nx9uzZUrer652e45mUlASgsNAp6sCBAwgJCYGiKMjNzcWyZctKHM/TTz+NZ599Vv27tXnbpk0bZGZmon379ujbt2+x+41Mz/E1u/27y0MPPYR77rkH7du3BwAEBQUVe46177ZG+D2r65NHde7cGZcuXcLFixfx5ZdfqsfSfPrpp1i9ejXc3Nxw8eJFXLx40eJ5JV3k+ODBgxg/fjyAwu6qJEkWz6tRo0aZD9Ru0KABAMDDwwPDhg3D3r17ERwcjPT0dPUx6enp6uOKPi8tLa3UxxidnuMGFF4T7KWXXsK6devg6vrP2s6GDRuwbNky/Pzzz8We4+3tjU6dOqFVq1YAAEmSkJycjLZt26Jhw4YAgOjoaItrng4dOhRDhw7FN998g5dffhnfffddmceoJ3qP5+28vb3RpEkTdbX43nvvxb59+xAVFaU+ZtOmTThz5gyOHTuGa9euISwsDAMGDFC/lC1btgwzZ860eN2S/t0YkdFiarZ48WIcPHjQ4nhLs5J+t37zzTeIiYlB/fr1iz0nLS0Nw4YNw6JFi9C8efNKj08reo/n66+/jjlz5mD69OlYunQppk2bBqD0eO7YsQMNGjSAn5+fxe3e3t4wmUzw8PCAj48P6tati6tXr1rsunjooYfwzDPPlHl8eqP3eN7u+vXrWL16NTZt2oStW7eW+LjWrVsjLi4OJ06cQFRUFAYNGgTA+jwsukg1evRorFmzBo888kiFx6glPcfztddew0cffVTsdm9vb/VcIgMHDsT69eutPv/VV1+Ft7e3uiBR0rxdunQpWrRogdWrVyM1NRVDhw7FH3/8UaYx6p2e4wtY/+4ydepUxMfHw8fHB1OnTsW3336LBx980OJ51r7b1qlTR71fr79ndV3YAsDYsWPx8ccfIzU1Fd27d0daWhq++OILJCUlITc3F+3atSt2Ihdvb2/1RAN79uxRb+/cuTNWrlyJZs2aAYB6wieznJwc9OvXr9gYwsLCMG/ePIvb0tPTUb9+fQghIMsyRo8eDQ8PD9SpUwcnTpxA69atsX79enz++ecWz+vTpw9eeuklZGdn4+bNmzhz5kyx7qAz0GvcUlJSMGXKFKxevdpiQWHr1q2YN28e1q9fb3Wblb+/P7Kzs3Ht2jXUrVsXe/fuxdixY5GRkYGaNWvCzc0NBw4cUL9cZWVlqa/j5eUFT0/PMv/s9Eiv8bTG3d0d7dq1Q2pqKnx9fbFr1y71JFC3j8/NzQ116tRBbm4u8vPzAQCXLl1CSkqKRVe2pH83RmakmALAt99+i1WrVmH16tVWFxZK+t26cOFC7N27F5s3b0ZycjIOHz6Mr7/+Go0bN8aQIUPw+uuvo1evXmUag57pNZ7m34UuLi6oV6+e+rvwTvHcu3cvkpKScM899+DYsWOoVasW/Pz8YDKZ8OOPP0IIgWvXriEtLQ1eXl64du0a6tWrB6Dw5FLt2rUr749QV/QaT2tSUlJw/fp1DBgwAFevXsW5c+ewcOFCi4Xe7OxsdeGwbt26qF27NgAgIyPD6jw0f8cCGE/AfvE8fvy4ugX23LlzmD59Oj7++GNER0dj7969CAsLw65duyy2tJq9/fbbOHv2rMWhWSXNWwDqdlcvLy9kZGSU7QdnEHqNb0nfXapVq6YuHjVq1MiiKQegxO+2hvg968gDeiviypUrwtPTU7zzzjtCCCEKCgrE8OHDRVBQkJg4caLo3r27+Pvvvy0OyD506JDo1q2bGDhwoJgxY4Z6oHNycrLo16+fMJlMwmQyiQ0bNlR4XA8//LAICgoSffr0sTgxUGJioggNDRXBwcHirbfeUm8fM2aM+ucvv/xSBAUFiaCgILuchEYPJ4/Sa9wiIyNF27ZtRWRkpIiMjBRr1qwRQgjh4+MjunTpot6+a9cuIYQQTz31lLh48aIQQogtW7aIsLAwERQUJObOnSuEEGLXrl2iW7duIjw8XISHh4vExEQhhBAffPCBiIyMFJIkif79+6sH6dtDVY6nLMsiOjpa1KxZU0RHR4vvvvtOCCFEUlKSkCRJhIaGiqlTp4qCggIhxD/zMC8vTzz88MMiJCREBAYGivfff199zQ8++EC89NJLFu9T0r8be3DUiS+MFNPs7GxRvXp10atXLzUGf/31lxCifL9bH374YfXkUbNnzxaNGjVSX+/111+v8JjvxBEnp9FrPB955BERGRkpwsLCxMSJE0VOTk6Z42l2+8ka33vvPREeHi569+6tnozq448/FoGBgSI8PFwMGTJEXLlypcJjvhNHnDxKr/Es6Xdu0fuLnlzGHM9t27aJ8PBw9feyeX6WNA9ffvll0bt3bxESEiIefvhhi5OQ2YojTx6l13gWVfRkQX///bfo37+/iIyMFCNGjFBP7mb+TnTixAnh4uIiwsLC1NjdHqOi8zYjI0Pcd999IiIiQgQGBqonZrQHLU4epdf4lvTd5bvvvlN/Xw4aNEjcuHFDCPHPfC3pu60jf8/erqxxdRGi8tetSExMRM+ePZGQkIAePXpU9uWoku4UD8bLuTCezoXxdD5fffUVHnroIcbUSRSdowA4Xw3KHMcVK1ZwfjoR5lDnVNa4GvtAMSIiIiIiIqryWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGZtPL/aSkpNjy5aiCyhoHxss5mOPIeDoHxtP5nDx5EgBj6iysxZGxNZ7bY8YYOgfmUOdU1nja5KzIp06dQocOHZCZmVnZlyIb8fT0REpKClq1alXsPsbL+bi6uqKgoEDrYZCNMJ7Ox83NTb1WMhmfOccCYD41ME9PT2zevBkxMTGMoRNhDnVOpdU2ZjYpbIHCYuny5cu2eCmygYYNG5YaeMbLuZw7dw4A1At6k7Exns4nOzsb7u7uWg+DbKRojmU+NS5zHBlD58Ic6pzuVNsANixsiYiIiIiIiLTAk0cRERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQWNgSERERERGRobGwJSIiIiIiIkNjYUtERERERESGxsKWiIiIiIiIDI2FLRERERERERkaC1siIiIiIiIyNBa2REREREREZGgsbImIiIiIiMjQ/g/QNdsvQNw/pQAAAABJRU5ErkJggg==", + "image/png": 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", "text/plain": [ "
" ] @@ -932,10 +932,10 @@ "id": "33fb7786", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.706833Z", - "iopub.status.busy": "2023-08-21T02:29:46.706699Z", - "iopub.status.idle": "2023-08-21T02:29:46.756824Z", - "shell.execute_reply": "2023-08-21T02:29:46.756520Z" + "iopub.execute_input": "2023-08-22T07:00:30.221897Z", + "iopub.status.busy": "2023-08-22T07:00:30.221737Z", + "iopub.status.idle": "2023-08-22T07:00:30.264092Z", + "shell.execute_reply": "2023-08-22T07:00:30.263767Z" } }, "outputs": [], @@ -967,10 +967,10 @@ "id": "a386755b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.758663Z", - "iopub.status.busy": "2023-08-21T02:29:46.758546Z", - "iopub.status.idle": "2023-08-21T02:29:46.761814Z", - "shell.execute_reply": "2023-08-21T02:29:46.761470Z" + "iopub.execute_input": "2023-08-22T07:00:30.265998Z", + "iopub.status.busy": "2023-08-22T07:00:30.265875Z", + "iopub.status.idle": "2023-08-22T07:00:30.268622Z", + "shell.execute_reply": "2023-08-22T07:00:30.268322Z" }, "lines_to_next_cell": 2 }, @@ -1013,10 +1013,10 @@ "id": "3d646928", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:46.763419Z", - "iopub.status.busy": "2023-08-21T02:29:46.763331Z", - "iopub.status.idle": "2023-08-21T02:29:47.049615Z", - "shell.execute_reply": "2023-08-21T02:29:47.049265Z" + "iopub.execute_input": "2023-08-22T07:00:30.270273Z", + "iopub.status.busy": "2023-08-22T07:00:30.270155Z", + "iopub.status.idle": "2023-08-22T07:00:30.522160Z", + "shell.execute_reply": "2023-08-22T07:00:30.521845Z" }, "lines_to_next_cell": 0 }, @@ -1074,10 +1074,10 @@ "id": "275feef7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:47.051447Z", - "iopub.status.busy": "2023-08-21T02:29:47.051323Z", - "iopub.status.idle": "2023-08-21T02:29:47.211049Z", - "shell.execute_reply": "2023-08-21T02:29:47.210740Z" + "iopub.execute_input": "2023-08-22T07:00:30.524138Z", + "iopub.status.busy": "2023-08-22T07:00:30.524014Z", + "iopub.status.idle": "2023-08-22T07:00:30.657807Z", + "shell.execute_reply": "2023-08-22T07:00:30.657403Z" }, "lines_to_next_cell": 2 }, @@ -1118,10 +1118,10 @@ "id": "01dbbef3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:47.212716Z", - "iopub.status.busy": "2023-08-21T02:29:47.212598Z", - "iopub.status.idle": "2023-08-21T02:29:47.305563Z", - "shell.execute_reply": "2023-08-21T02:29:47.305155Z" + "iopub.execute_input": "2023-08-22T07:00:30.660013Z", + "iopub.status.busy": "2023-08-22T07:00:30.659853Z", + "iopub.status.idle": "2023-08-22T07:00:30.742817Z", + "shell.execute_reply": "2023-08-22T07:00:30.742410Z" } }, "outputs": [ @@ -1171,10 +1171,10 @@ "id": "b75cc90e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:47.307949Z", - "iopub.status.busy": "2023-08-21T02:29:47.307809Z", - "iopub.status.idle": "2023-08-21T02:29:48.296516Z", - "shell.execute_reply": "2023-08-21T02:29:48.296211Z" + "iopub.execute_input": "2023-08-22T07:00:30.744837Z", + "iopub.status.busy": "2023-08-22T07:00:30.744692Z", + "iopub.status.idle": "2023-08-22T07:00:31.411169Z", + "shell.execute_reply": "2023-08-22T07:00:31.410861Z" }, "lines_to_next_cell": 0 }, @@ -1220,10 +1220,10 @@ "id": "bf9a5ed4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:48.298333Z", - "iopub.status.busy": "2023-08-21T02:29:48.298184Z", - "iopub.status.idle": "2023-08-21T02:29:48.412949Z", - "shell.execute_reply": "2023-08-21T02:29:48.412594Z" + "iopub.execute_input": "2023-08-22T07:00:31.412847Z", + "iopub.status.busy": "2023-08-22T07:00:31.412730Z", + "iopub.status.idle": "2023-08-22T07:00:31.503962Z", + "shell.execute_reply": "2023-08-22T07:00:31.503621Z" }, "lines_to_next_cell": 2 }, @@ -1263,10 +1263,10 @@ "id": "71316e9a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:48.414933Z", - "iopub.status.busy": "2023-08-21T02:29:48.414785Z", - "iopub.status.idle": "2023-08-21T02:29:48.422251Z", - "shell.execute_reply": "2023-08-21T02:29:48.421922Z" + "iopub.execute_input": "2023-08-22T07:00:31.505738Z", + "iopub.status.busy": "2023-08-22T07:00:31.505608Z", + "iopub.status.idle": "2023-08-22T07:00:31.511656Z", + "shell.execute_reply": "2023-08-22T07:00:31.511297Z" }, "lines_to_next_cell": 0 }, @@ -1421,10 +1421,10 @@ "id": "0bcc5ff1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:48.424109Z", - "iopub.status.busy": "2023-08-21T02:29:48.423996Z", - "iopub.status.idle": "2023-08-21T02:29:52.311829Z", - "shell.execute_reply": "2023-08-21T02:29:52.311492Z" + "iopub.execute_input": "2023-08-22T07:00:31.513595Z", + "iopub.status.busy": "2023-08-22T07:00:31.513453Z", + "iopub.status.idle": "2023-08-22T07:00:34.630915Z", + "shell.execute_reply": "2023-08-22T07:00:34.630577Z" } }, "outputs": [ @@ -1469,10 +1469,10 @@ "id": "060f47eb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:52.313643Z", - "iopub.status.busy": "2023-08-21T02:29:52.313522Z", - "iopub.status.idle": "2023-08-21T02:29:52.788145Z", - "shell.execute_reply": "2023-08-21T02:29:52.787823Z" + "iopub.execute_input": "2023-08-22T07:00:34.632952Z", + "iopub.status.busy": "2023-08-22T07:00:34.632784Z", + "iopub.status.idle": "2023-08-22T07:00:35.097134Z", + "shell.execute_reply": "2023-08-22T07:00:35.096800Z" } }, "outputs": [ @@ -1519,10 +1519,10 @@ "id": "43505dad", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:52.789753Z", - "iopub.status.busy": "2023-08-21T02:29:52.789632Z", - "iopub.status.idle": "2023-08-21T02:29:52.801529Z", - "shell.execute_reply": "2023-08-21T02:29:52.801234Z" + "iopub.execute_input": "2023-08-22T07:00:35.100329Z", + "iopub.status.busy": "2023-08-22T07:00:35.100143Z", + "iopub.status.idle": "2023-08-22T07:00:35.112033Z", + "shell.execute_reply": "2023-08-22T07:00:35.111605Z" } }, "outputs": [ @@ -1560,10 +1560,10 @@ "id": "c0a03126", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:52.803315Z", - "iopub.status.busy": "2023-08-21T02:29:52.803174Z", - "iopub.status.idle": "2023-08-21T02:29:55.330726Z", - "shell.execute_reply": "2023-08-21T02:29:55.330425Z" + "iopub.execute_input": "2023-08-22T07:00:35.113963Z", + "iopub.status.busy": "2023-08-22T07:00:35.113830Z", + "iopub.status.idle": "2023-08-22T07:00:37.129817Z", + "shell.execute_reply": "2023-08-22T07:00:37.129514Z" }, "lines_to_next_cell": 2 }, @@ -1627,10 +1627,10 @@ "id": "58f6e11f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:55.332677Z", - "iopub.status.busy": "2023-08-21T02:29:55.332550Z", - "iopub.status.idle": "2023-08-21T02:29:56.797204Z", - "shell.execute_reply": "2023-08-21T02:29:56.796899Z" + "iopub.execute_input": "2023-08-22T07:00:37.131701Z", + "iopub.status.busy": "2023-08-22T07:00:37.131582Z", + "iopub.status.idle": "2023-08-22T07:00:38.482392Z", + "shell.execute_reply": "2023-08-22T07:00:38.481994Z" }, "lines_to_next_cell": 2 }, @@ -1668,10 +1668,10 @@ "id": "a5b1296f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:56.798892Z", - "iopub.status.busy": "2023-08-21T02:29:56.798779Z", - "iopub.status.idle": "2023-08-21T02:29:57.098494Z", - "shell.execute_reply": "2023-08-21T02:29:57.098140Z" + "iopub.execute_input": "2023-08-22T07:00:38.485515Z", + "iopub.status.busy": "2023-08-22T07:00:38.485339Z", + "iopub.status.idle": "2023-08-22T07:00:38.830191Z", + "shell.execute_reply": "2023-08-22T07:00:38.829761Z" }, "lines_to_next_cell": 2 }, @@ -1707,10 +1707,10 @@ "id": "36c52755", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:57.100444Z", - "iopub.status.busy": "2023-08-21T02:29:57.100310Z", - "iopub.status.idle": "2023-08-21T02:29:57.103577Z", - "shell.execute_reply": "2023-08-21T02:29:57.103213Z" + "iopub.execute_input": "2023-08-22T07:00:38.832666Z", + "iopub.status.busy": "2023-08-22T07:00:38.832460Z", + "iopub.status.idle": "2023-08-22T07:00:38.836173Z", + "shell.execute_reply": "2023-08-22T07:00:38.835780Z" }, "lines_to_next_cell": 0 }, @@ -1759,7 +1759,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -1772,7 +1772,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch09-svm-lab.Rmd b/Ch09-svm-lab.Rmd index 0b653ef..e08f732 100644 --- a/Ch09-svm-lab.Rmd +++ b/Ch09-svm-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch09-svm-lab.ipynb b/Ch09-svm-lab.ipynb index bf1cc7c..3b96de8 100644 --- a/Ch09-svm-lab.ipynb +++ b/Ch09-svm-lab.ipynb @@ -28,10 +28,10 @@ "id": "3973b95f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:58.477582Z", - "iopub.status.busy": "2023-08-21T02:29:58.477467Z", - "iopub.status.idle": "2023-08-21T02:29:59.432527Z", - "shell.execute_reply": "2023-08-21T02:29:59.432225Z" + "iopub.execute_input": "2023-08-22T07:00:43.196408Z", + "iopub.status.busy": "2023-08-22T07:00:43.196299Z", + "iopub.status.idle": "2023-08-22T07:00:44.031971Z", + "shell.execute_reply": "2023-08-22T07:00:44.031635Z" }, "lines_to_next_cell": 0 }, @@ -58,10 +58,10 @@ "id": "0161e55e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.434432Z", - "iopub.status.busy": "2023-08-21T02:29:59.434258Z", - "iopub.status.idle": "2023-08-21T02:29:59.466972Z", - "shell.execute_reply": "2023-08-21T02:29:59.466647Z" + "iopub.execute_input": "2023-08-22T07:00:44.034329Z", + "iopub.status.busy": "2023-08-22T07:00:44.034140Z", + "iopub.status.idle": "2023-08-22T07:00:44.066591Z", + "shell.execute_reply": "2023-08-22T07:00:44.066283Z" } }, "outputs": [], @@ -86,10 +86,10 @@ "id": "7661b056", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.469128Z", - "iopub.status.busy": "2023-08-21T02:29:59.468999Z", - "iopub.status.idle": "2023-08-21T02:29:59.470961Z", - "shell.execute_reply": "2023-08-21T02:29:59.470667Z" + "iopub.execute_input": "2023-08-22T07:00:44.068359Z", + "iopub.status.busy": "2023-08-22T07:00:44.068256Z", + "iopub.status.idle": "2023-08-22T07:00:44.070030Z", + "shell.execute_reply": "2023-08-22T07:00:44.069763Z" } }, "outputs": [], @@ -126,10 +126,10 @@ "id": "46e9ab84", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.472867Z", - "iopub.status.busy": "2023-08-21T02:29:59.472726Z", - "iopub.status.idle": "2023-08-21T02:29:59.583508Z", - "shell.execute_reply": "2023-08-21T02:29:59.583126Z" + "iopub.execute_input": "2023-08-22T07:00:44.071771Z", + "iopub.status.busy": "2023-08-22T07:00:44.071636Z", + "iopub.status.idle": "2023-08-22T07:00:44.163199Z", + "shell.execute_reply": "2023-08-22T07:00:44.162710Z" }, "lines_to_next_cell": 0 }, @@ -171,10 +171,10 @@ "id": "605ffdc0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.585485Z", - "iopub.status.busy": "2023-08-21T02:29:59.585317Z", - "iopub.status.idle": "2023-08-21T02:29:59.590274Z", - "shell.execute_reply": "2023-08-21T02:29:59.589979Z" + "iopub.execute_input": "2023-08-22T07:00:44.165309Z", + "iopub.status.busy": "2023-08-22T07:00:44.165170Z", + "iopub.status.idle": "2023-08-22T07:00:44.169891Z", + "shell.execute_reply": "2023-08-22T07:00:44.169496Z" }, "lines_to_next_cell": 2 }, @@ -215,10 +215,10 @@ "id": "302a49a1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.591976Z", - "iopub.status.busy": "2023-08-21T02:29:59.591865Z", - "iopub.status.idle": "2023-08-21T02:29:59.734225Z", - "shell.execute_reply": "2023-08-21T02:29:59.733936Z" + "iopub.execute_input": "2023-08-22T07:00:44.171704Z", + "iopub.status.busy": "2023-08-22T07:00:44.171421Z", + "iopub.status.idle": "2023-08-22T07:00:44.323926Z", + "shell.execute_reply": "2023-08-22T07:00:44.323505Z" } }, "outputs": [ @@ -260,10 +260,10 @@ "id": "cc1d6a13", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.735943Z", - "iopub.status.busy": "2023-08-21T02:29:59.735816Z", - "iopub.status.idle": "2023-08-21T02:29:59.878335Z", - "shell.execute_reply": "2023-08-21T02:29:59.878032Z" + "iopub.execute_input": "2023-08-22T07:00:44.326070Z", + "iopub.status.busy": "2023-08-22T07:00:44.325931Z", + "iopub.status.idle": "2023-08-22T07:00:44.449908Z", + "shell.execute_reply": "2023-08-22T07:00:44.449566Z" }, "lines_to_next_cell": 0 }, @@ -306,10 +306,10 @@ "id": "6133c846", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.880078Z", - "iopub.status.busy": "2023-08-21T02:29:59.879965Z", - "iopub.status.idle": "2023-08-21T02:29:59.882347Z", - "shell.execute_reply": "2023-08-21T02:29:59.882070Z" + "iopub.execute_input": "2023-08-22T07:00:44.451882Z", + "iopub.status.busy": "2023-08-22T07:00:44.451759Z", + "iopub.status.idle": "2023-08-22T07:00:44.454360Z", + "shell.execute_reply": "2023-08-22T07:00:44.454092Z" }, "lines_to_next_cell": 2 }, @@ -344,10 +344,10 @@ "id": "9adb3793", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.883852Z", - "iopub.status.busy": "2023-08-21T02:29:59.883749Z", - "iopub.status.idle": "2023-08-21T02:29:59.910535Z", - "shell.execute_reply": "2023-08-21T02:29:59.910272Z" + "iopub.execute_input": "2023-08-22T07:00:44.456205Z", + "iopub.status.busy": "2023-08-22T07:00:44.456086Z", + "iopub.status.idle": "2023-08-22T07:00:44.482752Z", + "shell.execute_reply": "2023-08-22T07:00:44.482392Z" }, "lines_to_next_cell": 2 }, @@ -392,10 +392,10 @@ "id": "d3ab343e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.912005Z", - "iopub.status.busy": "2023-08-21T02:29:59.911925Z", - "iopub.status.idle": "2023-08-21T02:29:59.914189Z", - "shell.execute_reply": "2023-08-21T02:29:59.913943Z" + "iopub.execute_input": "2023-08-22T07:00:44.484837Z", + "iopub.status.busy": "2023-08-22T07:00:44.484685Z", + "iopub.status.idle": "2023-08-22T07:00:44.487229Z", + "shell.execute_reply": "2023-08-22T07:00:44.486932Z" }, "lines_to_next_cell": 0 }, @@ -433,10 +433,10 @@ "id": "6aba117e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.915563Z", - "iopub.status.busy": "2023-08-21T02:29:59.915487Z", - "iopub.status.idle": "2023-08-21T02:29:59.917323Z", - "shell.execute_reply": "2023-08-21T02:29:59.917078Z" + "iopub.execute_input": "2023-08-22T07:00:44.488910Z", + "iopub.status.busy": "2023-08-22T07:00:44.488789Z", + "iopub.status.idle": "2023-08-22T07:00:44.490857Z", + "shell.execute_reply": "2023-08-22T07:00:44.490592Z" } }, "outputs": [], @@ -462,10 +462,10 @@ "id": "dbe7d737", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.918744Z", - "iopub.status.busy": "2023-08-21T02:29:59.918666Z", - "iopub.status.idle": "2023-08-21T02:29:59.925361Z", - "shell.execute_reply": "2023-08-21T02:29:59.925039Z" + "iopub.execute_input": "2023-08-22T07:00:44.492721Z", + "iopub.status.busy": "2023-08-22T07:00:44.492565Z", + "iopub.status.idle": "2023-08-22T07:00:44.498024Z", + "shell.execute_reply": "2023-08-22T07:00:44.497699Z" } }, "outputs": [ @@ -549,10 +549,10 @@ "id": "ab1697c2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.927158Z", - "iopub.status.busy": "2023-08-21T02:29:59.927027Z", - "iopub.status.idle": "2023-08-21T02:29:59.931558Z", - "shell.execute_reply": "2023-08-21T02:29:59.931228Z" + "iopub.execute_input": "2023-08-22T07:00:44.499990Z", + "iopub.status.busy": "2023-08-22T07:00:44.499862Z", + "iopub.status.idle": "2023-08-22T07:00:44.504347Z", + "shell.execute_reply": "2023-08-22T07:00:44.504085Z" } }, "outputs": [ @@ -640,10 +640,10 @@ "id": "0fd42b1e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:59.933100Z", - "iopub.status.busy": "2023-08-21T02:29:59.933001Z", - "iopub.status.idle": "2023-08-21T02:30:00.054738Z", - "shell.execute_reply": "2023-08-21T02:30:00.054338Z" + "iopub.execute_input": "2023-08-22T07:00:44.506318Z", + "iopub.status.busy": "2023-08-22T07:00:44.506164Z", + "iopub.status.idle": "2023-08-22T07:00:44.587482Z", + "shell.execute_reply": "2023-08-22T07:00:44.587059Z" } }, "outputs": [ @@ -678,10 +678,10 @@ "id": "09c15299", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.056655Z", - "iopub.status.busy": "2023-08-21T02:30:00.056526Z", - "iopub.status.idle": "2023-08-21T02:30:00.061096Z", - "shell.execute_reply": "2023-08-21T02:30:00.060792Z" + "iopub.execute_input": "2023-08-22T07:00:44.589398Z", + "iopub.status.busy": "2023-08-22T07:00:44.589260Z", + "iopub.status.idle": "2023-08-22T07:00:44.594250Z", + "shell.execute_reply": "2023-08-22T07:00:44.593884Z" } }, "outputs": [ @@ -765,10 +765,10 @@ "id": "d5fd2ff9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.062673Z", - "iopub.status.busy": "2023-08-21T02:30:00.062585Z", - "iopub.status.idle": "2023-08-21T02:30:00.199860Z", - "shell.execute_reply": "2023-08-21T02:30:00.199129Z" + "iopub.execute_input": "2023-08-22T07:00:44.596069Z", + "iopub.status.busy": "2023-08-22T07:00:44.595957Z", + "iopub.status.idle": "2023-08-22T07:00:44.704810Z", + "shell.execute_reply": "2023-08-22T07:00:44.704515Z" }, "lines_to_next_cell": 0 }, @@ -810,10 +810,10 @@ "id": "39aff1b1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.202380Z", - "iopub.status.busy": "2023-08-21T02:30:00.202233Z", - "iopub.status.idle": "2023-08-21T02:30:00.207886Z", - "shell.execute_reply": "2023-08-21T02:30:00.207493Z" + "iopub.execute_input": "2023-08-22T07:00:44.706840Z", + "iopub.status.busy": "2023-08-22T07:00:44.706674Z", + "iopub.status.idle": "2023-08-22T07:00:44.711712Z", + "shell.execute_reply": "2023-08-22T07:00:44.711351Z" } }, "outputs": [ @@ -897,10 +897,10 @@ "id": "63a9d752", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.209907Z", - "iopub.status.busy": "2023-08-21T02:30:00.209781Z", - "iopub.status.idle": "2023-08-21T02:30:00.340803Z", - "shell.execute_reply": "2023-08-21T02:30:00.340433Z" + "iopub.execute_input": "2023-08-22T07:00:44.713664Z", + "iopub.status.busy": "2023-08-22T07:00:44.713515Z", + "iopub.status.idle": "2023-08-22T07:00:44.825679Z", + "shell.execute_reply": "2023-08-22T07:00:44.825364Z" }, "lines_to_next_cell": 2 }, @@ -950,10 +950,10 @@ "id": "2fee8df5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.342773Z", - "iopub.status.busy": "2023-08-21T02:30:00.342626Z", - "iopub.status.idle": "2023-08-21T02:30:00.345094Z", - "shell.execute_reply": "2023-08-21T02:30:00.344774Z" + "iopub.execute_input": "2023-08-22T07:00:44.827655Z", + "iopub.status.busy": "2023-08-22T07:00:44.827492Z", + "iopub.status.idle": "2023-08-22T07:00:44.829859Z", + "shell.execute_reply": "2023-08-22T07:00:44.829433Z" } }, "outputs": [], @@ -978,10 +978,10 @@ "id": "48f01abe", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.347053Z", - "iopub.status.busy": "2023-08-21T02:30:00.346902Z", - "iopub.status.idle": "2023-08-21T02:30:00.440453Z", - "shell.execute_reply": "2023-08-21T02:30:00.440153Z" + "iopub.execute_input": "2023-08-22T07:00:44.831676Z", + "iopub.status.busy": "2023-08-22T07:00:44.831542Z", + "iopub.status.idle": "2023-08-22T07:00:44.912763Z", + "shell.execute_reply": "2023-08-22T07:00:44.912396Z" }, "lines_to_next_cell": 2 }, @@ -989,7 +989,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 20, @@ -1031,10 +1031,10 @@ "id": "4acc3246", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.442257Z", - "iopub.status.busy": "2023-08-21T02:30:00.442156Z", - "iopub.status.idle": "2023-08-21T02:30:00.446674Z", - "shell.execute_reply": "2023-08-21T02:30:00.446369Z" + "iopub.execute_input": "2023-08-22T07:00:44.914642Z", + "iopub.status.busy": "2023-08-22T07:00:44.914493Z", + "iopub.status.idle": "2023-08-22T07:00:44.918862Z", + "shell.execute_reply": "2023-08-22T07:00:44.918577Z" } }, "outputs": [ @@ -1079,10 +1079,10 @@ "id": "e9852a28", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.448268Z", - "iopub.status.busy": "2023-08-21T02:30:00.448160Z", - "iopub.status.idle": "2023-08-21T02:30:00.828511Z", - "shell.execute_reply": "2023-08-21T02:30:00.828128Z" + "iopub.execute_input": "2023-08-22T07:00:44.920379Z", + "iopub.status.busy": "2023-08-22T07:00:44.920289Z", + "iopub.status.idle": "2023-08-22T07:00:45.229404Z", + "shell.execute_reply": "2023-08-22T07:00:45.229004Z" } }, "outputs": [ @@ -1123,10 +1123,10 @@ "id": "01232fc9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:00.830365Z", - "iopub.status.busy": "2023-08-21T02:30:00.830226Z", - "iopub.status.idle": "2023-08-21T02:30:01.132677Z", - "shell.execute_reply": "2023-08-21T02:30:01.132224Z" + "iopub.execute_input": "2023-08-22T07:00:45.231425Z", + "iopub.status.busy": "2023-08-22T07:00:45.231287Z", + "iopub.status.idle": "2023-08-22T07:00:45.394458Z", + "shell.execute_reply": "2023-08-22T07:00:45.394098Z" } }, "outputs": [ @@ -1167,10 +1167,10 @@ "id": "bcbd15a4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.134616Z", - "iopub.status.busy": "2023-08-21T02:30:01.134486Z", - "iopub.status.idle": "2023-08-21T02:30:01.243519Z", - "shell.execute_reply": "2023-08-21T02:30:01.243203Z" + "iopub.execute_input": "2023-08-22T07:00:45.396381Z", + "iopub.status.busy": "2023-08-22T07:00:45.396249Z", + "iopub.status.idle": "2023-08-22T07:00:45.487743Z", + "shell.execute_reply": "2023-08-22T07:00:45.487417Z" } }, "outputs": [ @@ -1215,10 +1215,10 @@ "id": "28ca551e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.245550Z", - "iopub.status.busy": "2023-08-21T02:30:01.245377Z", - "iopub.status.idle": "2023-08-21T02:30:01.600896Z", - "shell.execute_reply": "2023-08-21T02:30:01.600574Z" + "iopub.execute_input": "2023-08-22T07:00:45.489428Z", + "iopub.status.busy": "2023-08-22T07:00:45.489307Z", + "iopub.status.idle": "2023-08-22T07:00:45.761918Z", + "shell.execute_reply": "2023-08-22T07:00:45.761509Z" } }, "outputs": [ @@ -1349,10 +1349,10 @@ "id": "68ac9421", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.602740Z", - "iopub.status.busy": "2023-08-21T02:30:01.602614Z", - "iopub.status.idle": "2023-08-21T02:30:01.698620Z", - "shell.execute_reply": "2023-08-21T02:30:01.698322Z" + "iopub.execute_input": "2023-08-22T07:00:45.763931Z", + "iopub.status.busy": "2023-08-22T07:00:45.763759Z", + "iopub.status.idle": "2023-08-22T07:00:45.849017Z", + "shell.execute_reply": "2023-08-22T07:00:45.848298Z" }, "lines_to_next_cell": 0 }, @@ -1394,10 +1394,10 @@ "id": "f79a9e0a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.700479Z", - "iopub.status.busy": "2023-08-21T02:30:01.700347Z", - "iopub.status.idle": "2023-08-21T02:30:01.837479Z", - "shell.execute_reply": "2023-08-21T02:30:01.837102Z" + "iopub.execute_input": "2023-08-22T07:00:45.851590Z", + "iopub.status.busy": "2023-08-22T07:00:45.851425Z", + "iopub.status.idle": "2023-08-22T07:00:45.979876Z", + "shell.execute_reply": "2023-08-22T07:00:45.979437Z" } }, "outputs": [ @@ -1443,10 +1443,10 @@ "id": "bdb9e503", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.839390Z", - "iopub.status.busy": "2023-08-21T02:30:01.839243Z", - "iopub.status.idle": "2023-08-21T02:30:01.843595Z", - "shell.execute_reply": "2023-08-21T02:30:01.843287Z" + "iopub.execute_input": "2023-08-22T07:00:45.982037Z", + "iopub.status.busy": "2023-08-22T07:00:45.981884Z", + "iopub.status.idle": "2023-08-22T07:00:45.986135Z", + "shell.execute_reply": "2023-08-22T07:00:45.985717Z" } }, "outputs": [], @@ -1474,10 +1474,10 @@ "id": "329f5d2c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.845300Z", - "iopub.status.busy": "2023-08-21T02:30:01.845201Z", - "iopub.status.idle": "2023-08-21T02:30:01.944073Z", - "shell.execute_reply": "2023-08-21T02:30:01.943763Z" + "iopub.execute_input": "2023-08-22T07:00:45.988269Z", + "iopub.status.busy": "2023-08-22T07:00:45.988146Z", + "iopub.status.idle": "2023-08-22T07:00:46.085414Z", + "shell.execute_reply": "2023-08-22T07:00:46.084883Z" } }, "outputs": [ @@ -1529,10 +1529,10 @@ "id": "267e113d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:01.945725Z", - "iopub.status.busy": "2023-08-21T02:30:01.945611Z", - "iopub.status.idle": "2023-08-21T02:30:02.034378Z", - "shell.execute_reply": "2023-08-21T02:30:02.034069Z" + "iopub.execute_input": "2023-08-22T07:00:46.087864Z", + "iopub.status.busy": "2023-08-22T07:00:46.087700Z", + "iopub.status.idle": "2023-08-22T07:00:46.169591Z", + "shell.execute_reply": "2023-08-22T07:00:46.169145Z" } }, "outputs": [ @@ -1570,10 +1570,10 @@ "id": "64cbebd0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:02.036083Z", - "iopub.status.busy": "2023-08-21T02:30:02.035963Z", - "iopub.status.idle": "2023-08-21T02:30:03.015535Z", - "shell.execute_reply": "2023-08-21T02:30:03.014798Z" + "iopub.execute_input": "2023-08-22T07:00:46.171760Z", + "iopub.status.busy": "2023-08-22T07:00:46.171615Z", + "iopub.status.idle": "2023-08-22T07:00:46.921038Z", + "shell.execute_reply": "2023-08-22T07:00:46.920658Z" }, "lines_to_next_cell": 0 }, @@ -1634,10 +1634,10 @@ "id": "b6e6f12b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:03.017430Z", - "iopub.status.busy": "2023-08-21T02:30:03.017293Z", - "iopub.status.idle": "2023-08-21T02:30:03.099156Z", - "shell.execute_reply": "2023-08-21T02:30:03.098760Z" + "iopub.execute_input": "2023-08-22T07:00:46.923126Z", + "iopub.status.busy": "2023-08-22T07:00:46.922983Z", + "iopub.status.idle": "2023-08-22T07:00:46.997998Z", + "shell.execute_reply": "2023-08-22T07:00:46.997721Z" } }, "outputs": [ @@ -1680,10 +1680,10 @@ "id": "273a10b2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:03.101069Z", - "iopub.status.busy": "2023-08-21T02:30:03.100881Z", - "iopub.status.idle": "2023-08-21T02:30:03.130224Z", - "shell.execute_reply": "2023-08-21T02:30:03.129845Z" + "iopub.execute_input": "2023-08-22T07:00:47.000124Z", + "iopub.status.busy": "2023-08-22T07:00:46.999957Z", + "iopub.status.idle": "2023-08-22T07:00:47.027848Z", + "shell.execute_reply": "2023-08-22T07:00:47.027461Z" } }, "outputs": [ @@ -1794,10 +1794,10 @@ "id": "bc3079a7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:03.132111Z", - "iopub.status.busy": "2023-08-21T02:30:03.131975Z", - "iopub.status.idle": "2023-08-21T02:30:03.143298Z", - "shell.execute_reply": "2023-08-21T02:30:03.142948Z" + "iopub.execute_input": "2023-08-22T07:00:47.030032Z", + "iopub.status.busy": "2023-08-22T07:00:47.029880Z", + "iopub.status.idle": "2023-08-22T07:00:47.040946Z", + "shell.execute_reply": "2023-08-22T07:00:47.040538Z" } }, "outputs": [ @@ -1900,7 +1900,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -1913,7 +1913,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch10-deeplearning-lab.Rmd b/Ch10-deeplearning-lab.Rmd index 51674b6..ce234b5 100644 --- a/Ch10-deeplearning-lab.Rmd +++ b/Ch10-deeplearning-lab.Rmd @@ -1,3 +1,19 @@ +--- +jupyter: + jupytext: + cell_metadata_filter: -all + formats: Rmd,ipynb + text_representation: + extension: .Rmd + format_name: rmarkdown + format_version: '1.2' + jupytext_version: 1.14.7 + kernelspec: + display_name: Python 3 (ipykernel) + language: python + name: python3 +--- + # Chapter 10 diff --git a/Ch10-deeplearning-lab.ipynb b/Ch10-deeplearning-lab.ipynb index 2577eac..4c5a709 100644 --- a/Ch10-deeplearning-lab.ipynb +++ b/Ch10-deeplearning-lab.ipynb @@ -26,6 +26,12 @@ "execution_count": 1, "id": "cf431f3f", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:23.822772Z", + "iopub.status.busy": "2023-08-22T06:36:23.822498Z", + "iopub.status.idle": "2023-08-22T06:36:35.889421Z", + "shell.execute_reply": "2023-08-22T06:36:35.888914Z" + }, "lines_to_next_cell": 2 }, "outputs": [], @@ -62,7 +68,14 @@ "cell_type": "code", "execution_count": 2, "id": "1db00e03", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:35.892370Z", + "iopub.status.busy": "2023-08-22T06:36:35.892133Z", + "iopub.status.idle": "2023-08-22T06:36:37.554519Z", + "shell.execute_reply": "2023-08-22T06:36:37.554232Z" + } + }, "outputs": [], "source": [ "import torch\n", @@ -88,7 +101,14 @@ "cell_type": "code", "execution_count": 3, "id": "3da0a445", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:37.556320Z", + "iopub.status.busy": "2023-08-22T06:36:37.556190Z", + "iopub.status.idle": "2023-08-22T06:36:38.312094Z", + "shell.execute_reply": "2023-08-22T06:36:38.311799Z" + } + }, "outputs": [], "source": [ "from torchmetrics import (MeanAbsoluteError,\n", @@ -112,7 +132,14 @@ "cell_type": "code", "execution_count": 4, "id": "bbbf32fe", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.313997Z", + "iopub.status.busy": "2023-08-22T06:36:38.313882Z", + "iopub.status.idle": "2023-08-22T06:36:38.557850Z", + "shell.execute_reply": "2023-08-22T06:36:38.557519Z" + } + }, "outputs": [], "source": [ "from pytorch_lightning import Trainer\n", @@ -132,7 +159,14 @@ "cell_type": "code", "execution_count": 5, "id": "3810caf4", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.559742Z", + "iopub.status.busy": "2023-08-22T06:36:38.559626Z", + "iopub.status.idle": "2023-08-22T06:36:38.563148Z", + "shell.execute_reply": "2023-08-22T06:36:38.562883Z" + } + }, "outputs": [ { "name": "stderr", @@ -163,6 +197,12 @@ "execution_count": 6, "id": "454dc419", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.564731Z", + "iopub.status.busy": "2023-08-22T06:36:38.564619Z", + "iopub.status.idle": "2023-08-22T06:36:38.566404Z", + "shell.execute_reply": "2023-08-22T06:36:38.566156Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -198,7 +238,14 @@ "cell_type": "code", "execution_count": 7, "id": "cd43a4c6", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.567754Z", + "iopub.status.busy": "2023-08-22T06:36:38.567677Z", + "iopub.status.idle": "2023-08-22T06:36:38.569838Z", + "shell.execute_reply": "2023-08-22T06:36:38.569588Z" + } + }, "outputs": [], "source": [ "from ISLP.torch import (SimpleDataModule,\n", @@ -227,7 +274,14 @@ "cell_type": "code", "execution_count": 8, "id": "eaf84e9c", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.571182Z", + "iopub.status.busy": "2023-08-22T06:36:38.571106Z", + "iopub.status.idle": "2023-08-22T06:36:38.572982Z", + "shell.execute_reply": "2023-08-22T06:36:38.572746Z" + } + }, "outputs": [], "source": [ "from ISLP.torch.imdb import (load_lookup,\n", @@ -257,6 +311,12 @@ "execution_count": 9, "id": "d007a49b", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.574407Z", + "iopub.status.busy": "2023-08-22T06:36:38.574330Z", + "iopub.status.idle": "2023-08-22T06:36:38.575831Z", + "shell.execute_reply": "2023-08-22T06:36:38.575582Z" + }, "lines_to_next_cell": 2 }, "outputs": [], @@ -279,6 +339,12 @@ "execution_count": 10, "id": "9da64364", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.577295Z", + "iopub.status.busy": "2023-08-22T06:36:38.577214Z", + "iopub.status.idle": "2023-08-22T06:36:38.582891Z", + "shell.execute_reply": "2023-08-22T06:36:38.582646Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -307,6 +373,12 @@ "execution_count": 11, "id": "a2cfe999", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.584411Z", + "iopub.status.busy": "2023-08-22T06:36:38.584330Z", + "iopub.status.idle": "2023-08-22T06:36:38.602242Z", + "shell.execute_reply": "2023-08-22T06:36:38.601986Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -342,7 +414,14 @@ "cell_type": "code", "execution_count": 12, "id": "5c600069", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.603814Z", + "iopub.status.busy": "2023-08-22T06:36:38.603735Z", + "iopub.status.idle": "2023-08-22T06:36:38.605828Z", + "shell.execute_reply": "2023-08-22T06:36:38.605618Z" + } + }, "outputs": [], "source": [ "(X_train, \n", @@ -367,7 +446,14 @@ "cell_type": "code", "execution_count": 13, "id": "6ea4f551", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.607262Z", + "iopub.status.busy": "2023-08-22T06:36:38.607183Z", + "iopub.status.idle": "2023-08-22T06:36:38.611049Z", + "shell.execute_reply": "2023-08-22T06:36:38.610800Z" + } + }, "outputs": [ { "data": { @@ -403,7 +489,14 @@ "cell_type": "code", "execution_count": 14, "id": "f1b8b3f5", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.612499Z", + "iopub.status.busy": "2023-08-22T06:36:38.612413Z", + "iopub.status.idle": "2023-08-22T06:36:38.614248Z", + "shell.execute_reply": "2023-08-22T06:36:38.614031Z" + } + }, "outputs": [], "source": [ "scaler = StandardScaler(with_mean=True, with_std=True)\n", @@ -427,6 +520,12 @@ "execution_count": 15, "id": "50ce4171", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.615637Z", + "iopub.status.busy": "2023-08-22T06:36:38.615534Z", + "iopub.status.idle": "2023-08-22T06:36:38.617783Z", + "shell.execute_reply": "2023-08-22T06:36:38.617551Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -451,7 +550,14 @@ "cell_type": "code", "execution_count": 16, "id": "94c4ab75", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:38.619363Z", + "iopub.status.busy": "2023-08-22T06:36:38.619259Z", + "iopub.status.idle": "2023-08-22T06:36:50.960206Z", + "shell.execute_reply": "2023-08-22T06:36:50.959901Z" + } + }, "outputs": [], "source": [ "cv = KFold(10,\n", @@ -479,6 +585,12 @@ "execution_count": 17, "id": "86e45999", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.962061Z", + "iopub.status.busy": "2023-08-22T06:36:50.961947Z", + "iopub.status.idle": "2023-08-22T06:36:50.964427Z", + "shell.execute_reply": "2023-08-22T06:36:50.964181Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -520,7 +632,14 @@ "cell_type": "code", "execution_count": 18, "id": "00ac7606", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.965887Z", + "iopub.status.busy": "2023-08-22T06:36:50.965780Z", + "iopub.status.idle": "2023-08-22T06:36:50.967993Z", + "shell.execute_reply": "2023-08-22T06:36:50.967736Z" + } + }, "outputs": [], "source": [ "class HittersModel(nn.Module):\n", @@ -578,7 +697,14 @@ "cell_type": "code", "execution_count": 19, "id": "bb7ff7e9", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.969396Z", + "iopub.status.busy": "2023-08-22T06:36:50.969288Z", + "iopub.status.idle": "2023-08-22T06:36:50.971584Z", + "shell.execute_reply": "2023-08-22T06:36:50.971363Z" + } + }, "outputs": [], "source": [ "hit_model = HittersModel(X.shape[1])\n" @@ -614,6 +740,12 @@ "execution_count": 20, "id": "b60d34e1", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.973300Z", + "iopub.status.busy": "2023-08-22T06:36:50.973196Z", + "iopub.status.idle": "2023-08-22T06:36:50.979604Z", + "shell.execute_reply": "2023-08-22T06:36:50.979367Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -634,7 +766,7 @@ "Total params: 1,051\n", "Trainable params: 1,051\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.MEGABYTES): 0.18\n", + "Total mult-adds (M): 0.18\n", "===================================================================================================================\n", "Input size (MB): 0.01\n", "Forward/backward pass size (MB): 0.07\n", @@ -682,6 +814,12 @@ "execution_count": 21, "id": "42f63682", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.981129Z", + "iopub.status.busy": "2023-08-22T06:36:50.981043Z", + "iopub.status.idle": "2023-08-22T06:36:50.983074Z", + "shell.execute_reply": "2023-08-22T06:36:50.982803Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -703,7 +841,14 @@ "cell_type": "code", "execution_count": 22, "id": "57fbf564", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.984595Z", + "iopub.status.busy": "2023-08-22T06:36:50.984509Z", + "iopub.status.idle": "2023-08-22T06:36:50.986442Z", + "shell.execute_reply": "2023-08-22T06:36:50.986202Z" + } + }, "outputs": [], "source": [ "X_test_t = torch.tensor(X_test.astype(np.float32))\n", @@ -738,7 +883,14 @@ "cell_type": "code", "execution_count": 23, "id": "570bdd73", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.987814Z", + "iopub.status.busy": "2023-08-22T06:36:50.987734Z", + "iopub.status.idle": "2023-08-22T06:36:50.989404Z", + "shell.execute_reply": "2023-08-22T06:36:50.989173Z" + } + }, "outputs": [], "source": [ "max_num_workers = rec_num_workers()" @@ -770,7 +922,14 @@ "cell_type": "code", "execution_count": 24, "id": "c08a4d6d", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.990908Z", + "iopub.status.busy": "2023-08-22T06:36:50.990826Z", + "iopub.status.idle": "2023-08-22T06:36:50.992776Z", + "shell.execute_reply": "2023-08-22T06:36:50.992504Z" + } + }, "outputs": [], "source": [ "hit_dm = SimpleDataModule(hit_train,\n", @@ -798,7 +957,14 @@ "cell_type": "code", "execution_count": 25, "id": "aaa1e593", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.994186Z", + "iopub.status.busy": "2023-08-22T06:36:50.994113Z", + "iopub.status.idle": "2023-08-22T06:36:50.996729Z", + "shell.execute_reply": "2023-08-22T06:36:50.996486Z" + } + }, "outputs": [], "source": [ "hit_module = SimpleModule.regression(hit_model,\n", @@ -825,7 +991,14 @@ "cell_type": "code", "execution_count": 26, "id": "1a4e9b3c", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:50.998209Z", + "iopub.status.busy": "2023-08-22T06:36:50.998126Z", + "iopub.status.idle": "2023-08-22T06:36:51.000007Z", + "shell.execute_reply": "2023-08-22T06:36:50.999781Z" + } + }, "outputs": [], "source": [ "hit_logger = CSVLogger('logs', name='hitters')" @@ -857,6 +1030,12 @@ "execution_count": 27, "id": "2f839fde", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:51.001398Z", + "iopub.status.busy": "2023-08-22T06:36:51.001321Z", + "iopub.status.idle": "2023-08-22T06:36:57.231774Z", + "shell.execute_reply": "2023-08-22T06:36:57.231473Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -883,7 +1062,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "57f1417773bf4bab9e04d2641c7de91f", "version_major": 2, "version_minor": 0 }, @@ -897,7 +1076,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3f81045e13e641428a7f37ab7ceb43be", + "model_id": "4c234bd07745482e823334ca8ede4b72", "version_major": 2, "version_minor": 0 }, @@ -911,7 +1090,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8a343e9ea8e847dda642f290345ce416", "version_major": 2, "version_minor": 0 }, @@ -925,7 +1104,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "cd4b335bd692418aaa6aeaf512b165a5", "version_major": 2, "version_minor": 0 }, @@ -939,7 +1118,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "3de010d447e14f7885ad82380d0ed23d", "version_major": 2, "version_minor": 0 }, @@ -953,7 +1132,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6437dc82d36048c0aa6e29d7179b802d", "version_major": 2, "version_minor": 0 }, @@ -967,7 +1146,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "31a48327218d49048a5164d4891693c1", "version_major": 2, "version_minor": 0 }, @@ -981,7 +1160,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "f5c7646fdcdf49069bcb0dd9a71f706d", "version_major": 2, "version_minor": 0 }, @@ -995,7 +1174,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "be384b3fd24f4e57b61662c11fcf8d3a", "version_major": 2, "version_minor": 0 }, @@ -1009,7 +1188,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "fc6b10ac7dd345a9845b6e8c544fbb13", "version_major": 2, "version_minor": 0 }, @@ -1023,7 +1202,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2c1faeb221e74ea98b1ad4098608e47a", "version_major": 2, "version_minor": 0 }, @@ -1037,7 +1216,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "84061abe2bb84c13b533440db38ca93c", "version_major": 2, "version_minor": 0 }, @@ -1051,7 +1230,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e10316b8ba324e97a57db50873e5dca7", "version_major": 2, "version_minor": 0 }, @@ -1065,7 +1244,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2b7ce659cfab4b5897b5f6a37d845569", "version_major": 2, "version_minor": 0 }, @@ -1079,7 +1258,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c8fc8ef9a49a4a4aba32b36fd942faa7", "version_major": 2, "version_minor": 0 }, @@ -1093,7 +1272,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "1ecb329931844b47b9b767b3c80b5e32", "version_major": 2, "version_minor": 0 }, @@ -1107,7 +1286,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "bdcc0adc6f664fdeb8e0b9ac5a8c351b", "version_major": 2, "version_minor": 0 }, @@ -1121,7 +1300,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e780afe5ba184f3b9cb0af6732f8a464", "version_major": 2, "version_minor": 0 }, @@ -1135,7 +1314,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c690985141334d6cb5927b912433934f", "version_major": 2, "version_minor": 0 }, @@ -1149,7 +1328,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "7573d869f1624ee5bedca0df253c3258", "version_major": 2, "version_minor": 0 }, @@ -1163,7 +1342,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "38b1b0db2ada465797993f95bcdedf1a", "version_major": 2, "version_minor": 0 }, @@ -1177,7 +1356,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a9778179731a4b1f88c81feda8dcfcc4", "version_major": 2, "version_minor": 0 }, @@ -1191,7 +1370,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a86f93dfbb57426bbc945995748d77a4", "version_major": 2, "version_minor": 0 }, @@ -1205,7 +1384,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4b66b4428ce34557934ea32daf3c1e23", "version_major": 2, "version_minor": 0 }, @@ -1219,7 +1398,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "95e913a4d43b405ab89dc36f65d1a62a", "version_major": 2, "version_minor": 0 }, @@ -1233,7 +1412,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "40b1b46633d74bbfb37ffe764573083f", "version_major": 2, "version_minor": 0 }, @@ -1247,7 +1426,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "705e9608333240d0b9e0fcb3ce46b936", "version_major": 2, "version_minor": 0 }, @@ -1261,7 +1440,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ac03f7c299544d9782de7c690c2732bb", "version_major": 2, "version_minor": 0 }, @@ -1275,7 +1454,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c27fdee8a15544c5991535a6a91f23b5", "version_major": 2, "version_minor": 0 }, @@ -1289,7 +1468,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8d04173d877f40278c2c38fecf03f347", "version_major": 2, "version_minor": 0 }, @@ -1303,7 +1482,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4b44d0b98185429ca36376fd9bdd5290", "version_major": 2, "version_minor": 0 }, @@ -1317,7 +1496,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "efe93a27bde349f5a17664bb31036ccb", "version_major": 2, "version_minor": 0 }, @@ -1331,7 +1510,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6959784ed10246328e8d93ad8d4a3199", "version_major": 2, "version_minor": 0 }, @@ -1345,7 +1524,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e3351d9c3ee8411b968bef75e03cd8a3", "version_major": 2, "version_minor": 0 }, @@ -1359,7 +1538,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "bce44e02e5df444fbffb7d9584c91654", "version_major": 2, "version_minor": 0 }, @@ -1373,7 +1552,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b438f2d5ab2e4dcd807c83bf9f9590e3", "version_major": 2, "version_minor": 0 }, @@ -1387,7 +1566,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e3861a097df54b019bbb8679c5998d55", "version_major": 2, "version_minor": 0 }, @@ -1401,7 +1580,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "90b4d7b3e5f54a33bd8f45b1db5ac9a5", "version_major": 2, "version_minor": 0 }, @@ -1415,7 +1594,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "d8934eb8b16f4a0ca89d18a2ea942c2b", "version_major": 2, "version_minor": 0 }, @@ -1429,7 +1608,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8fa19f79b5b24960a0406b57aec15d97", "version_major": 2, "version_minor": 0 }, @@ -1443,7 +1622,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "47fc7a6d129c4fbe8ffeec0ae5462473", "version_major": 2, "version_minor": 0 }, @@ -1457,7 +1636,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "7db3b75a263f4ddda899eb29f5cfaef3", "version_major": 2, "version_minor": 0 }, @@ -1471,7 +1650,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "26e3ef4daa1040c08318f410c9ce7301", "version_major": 2, "version_minor": 0 }, @@ -1485,7 +1664,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2757386cc60944f8882392a13593aea3", "version_major": 2, "version_minor": 0 }, @@ -1499,7 +1678,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4b978e6606314196ab8e5357263bdf46", "version_major": 2, "version_minor": 0 }, @@ -1513,7 +1692,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "35250da3c5d24ac6be004b8377f0471f", "version_major": 2, "version_minor": 0 }, @@ -1527,7 +1706,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "595bb83f8eda4b4bad9cc570604cfeda", "version_major": 2, "version_minor": 0 }, @@ -1541,7 +1720,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "1533565239a74701823302f09bf1bc44", "version_major": 2, "version_minor": 0 }, @@ -1555,7 +1734,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "336786699ff5436da313a46db847fab4", "version_major": 2, "version_minor": 0 }, @@ -1569,7 +1748,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "553e586e7cd54ad3bb9e01d0fc37754e", + "model_id": "cf95bde69fa14a1eb0a348a4c394f678", "version_major": 2, "version_minor": 0 }, @@ -1583,7 +1762,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "05c22b9bdd4c48098756a37b57fc963b", + "model_id": "7aca029ff1bd4a159fa095fe2a761a79", "version_major": 2, "version_minor": 0 }, @@ -1597,7 +1776,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f073bf03d90b4e318352c5de82bb9953", + "model_id": "99ec7e76a90e4d32aa129b8a5432f9b1", "version_major": 2, "version_minor": 0 }, @@ -1645,13 +1824,19 @@ "execution_count": 28, "id": "672b4410", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:57.233763Z", + "iopub.status.busy": "2023-08-22T06:36:57.233589Z", + "iopub.status.idle": "2023-08-22T06:36:58.499876Z", + "shell.execute_reply": "2023-08-22T06:36:58.499595Z" + }, "lines_to_next_cell": 2 }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.501449Z", + "iopub.status.busy": "2023-08-22T06:36:58.501342Z", + "iopub.status.idle": "2023-08-22T06:36:58.505142Z", + "shell.execute_reply": "2023-08-22T06:36:58.504888Z" + } + }, "outputs": [], "source": [ "hit_results = pd.read_csv(hit_logger.experiment.metrics_file_path)" @@ -1741,6 +1920,12 @@ "execution_count": 30, "id": "67ce1e26", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.506556Z", + "iopub.status.busy": "2023-08-22T06:36:58.506485Z", + "iopub.status.idle": "2023-08-22T06:36:58.508767Z", + "shell.execute_reply": "2023-08-22T06:36:58.508514Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -1784,6 +1969,12 @@ "execution_count": 31, "id": "deb684d2", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.510129Z", + "iopub.status.busy": "2023-08-22T06:36:58.510060Z", + "iopub.status.idle": "2023-08-22T06:36:58.709656Z", + "shell.execute_reply": "2023-08-22T06:36:58.700996Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -1831,6 +2022,12 @@ "execution_count": 32, "id": "454033dd", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.732799Z", + "iopub.status.busy": "2023-08-22T06:36:58.729950Z", + "iopub.status.idle": "2023-08-22T06:36:58.780581Z", + "shell.execute_reply": "2023-08-22T06:36:58.765673Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -1877,6 +2074,12 @@ "execution_count": 33, "id": "71b3d0d0", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.807133Z", + "iopub.status.busy": "2023-08-22T06:36:58.800859Z", + "iopub.status.idle": "2023-08-22T06:36:58.836318Z", + "shell.execute_reply": "2023-08-22T06:36:58.822052Z" + }, "lines_to_next_cell": 2 }, "outputs": [], @@ -1909,7 +2112,14 @@ "cell_type": "code", "execution_count": 34, "id": "def8605c", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.852033Z", + "iopub.status.busy": "2023-08-22T06:36:58.848358Z", + "iopub.status.idle": "2023-08-22T06:36:58.873333Z", + "shell.execute_reply": "2023-08-22T06:36:58.873077Z" + } + }, "outputs": [ { "data": { @@ -1964,7 +2174,14 @@ "cell_type": "code", "execution_count": 35, "id": "8b9e2b8c", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.874850Z", + "iopub.status.busy": "2023-08-22T06:36:58.874776Z", + "iopub.status.idle": "2023-08-22T06:36:58.877600Z", + "shell.execute_reply": "2023-08-22T06:36:58.877374Z" + } + }, "outputs": [], "source": [ "mnist_dm = SimpleDataModule(mnist_train,\n", @@ -1988,6 +2205,12 @@ "execution_count": 36, "id": "a4b95dc6", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:36:58.879121Z", + "iopub.status.busy": "2023-08-22T06:36:58.879027Z", + "iopub.status.idle": "2023-08-22T06:37:01.493098Z", + "shell.execute_reply": "2023-08-22T06:37:01.492695Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -2026,7 +2249,14 @@ "cell_type": "code", "execution_count": 37, "id": "17714c25", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:37:01.495059Z", + "iopub.status.busy": "2023-08-22T06:37:01.494927Z", + "iopub.status.idle": "2023-08-22T06:37:01.497746Z", + "shell.execute_reply": "2023-08-22T06:37:01.497412Z" + } + }, "outputs": [], "source": [ "class MNISTModel(nn.Module):\n", @@ -2066,7 +2296,14 @@ "cell_type": "code", "execution_count": 38, "id": "88a4bf46", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:37:01.499269Z", + "iopub.status.busy": "2023-08-22T06:37:01.499164Z", + "iopub.status.idle": "2023-08-22T06:37:01.501783Z", + "shell.execute_reply": "2023-08-22T06:37:01.501554Z" + } + }, "outputs": [], "source": [ "mnist_model = MNISTModel()\n" @@ -2085,7 +2322,14 @@ "cell_type": "code", "execution_count": 39, "id": "ea0d9387", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:37:01.503288Z", + "iopub.status.busy": "2023-08-22T06:37:01.503188Z", + "iopub.status.idle": "2023-08-22T06:37:01.506547Z", + "shell.execute_reply": "2023-08-22T06:37:01.506292Z" + } + }, "outputs": [ { "data": { @@ -2116,7 +2360,14 @@ "cell_type": "code", "execution_count": 40, "id": "17c34a29", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:37:01.507963Z", + "iopub.status.busy": "2023-08-22T06:37:01.507888Z", + "iopub.status.idle": "2023-08-22T06:37:01.511369Z", + "shell.execute_reply": "2023-08-22T06:37:01.511148Z" + } + }, "outputs": [ { "data": { @@ -2140,7 +2391,7 @@ "Total params: 235,146\n", "Trainable params: 235,146\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.MEGABYTES): 60.20\n", + "Total mult-adds (M): 60.20\n", "===================================================================================================================\n", "Input size (MB): 0.80\n", "Forward/backward pass size (MB): 0.81\n", @@ -2178,7 +2429,14 @@ "cell_type": "code", "execution_count": 41, "id": "a0608bd1", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:37:01.512793Z", + "iopub.status.busy": "2023-08-22T06:37:01.512716Z", + "iopub.status.idle": "2023-08-22T06:37:01.515484Z", + "shell.execute_reply": "2023-08-22T06:37:01.515264Z" + } + }, "outputs": [], "source": [ "mnist_module = SimpleModule.classification(mnist_model,\n", @@ -2199,6 +2457,12 @@ "execution_count": 42, "id": "cf8e3d9d", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:37:01.516943Z", + "iopub.status.busy": "2023-08-22T06:37:01.516871Z", + "iopub.status.idle": "2023-08-22T06:37:52.281809Z", + "shell.execute_reply": "2023-08-22T06:37:52.281494Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -2225,7 +2489,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "63df57862e174cfbac1b87dcdce84e5b", "version_major": 2, "version_minor": 0 }, @@ -2239,7 +2503,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2c7fc7b3fc61455b88cf7020ce62d19e", + "model_id": "0c8fa4bf11bc406ca04772133304a80b", "version_major": 2, "version_minor": 0 }, @@ -2253,7 +2517,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "286d40af4ac7465fa859e111186e92a2", "version_major": 2, "version_minor": 0 }, @@ -2267,7 +2531,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b34683237d33463fb3e956721f9e93a0", "version_major": 2, "version_minor": 0 }, @@ -2281,7 +2545,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8f17ac7cff5a42238da4984e05d2d712", "version_major": 2, "version_minor": 0 }, @@ -2295,7 +2559,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "856884c4ba3140fbbb44c8d3860be17d", "version_major": 2, "version_minor": 0 }, @@ -2309,7 +2573,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "9ed1badd6c7f42458216610a2bd88f1d", "version_major": 2, "version_minor": 0 }, @@ -2323,7 +2587,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a27211d050d742dda389aaaa17816a49", "version_major": 2, "version_minor": 0 }, @@ -2337,7 +2601,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "dced6bafd5f243d981b97c504f026b7f", "version_major": 2, "version_minor": 0 }, @@ -2351,7 +2615,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "86b5e3b7319948c58d1a0f287a6a4270", "version_major": 2, "version_minor": 0 }, @@ -2365,7 +2629,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ab0715c2a7f1471880888a605ab86282", "version_major": 2, "version_minor": 0 }, @@ -2379,7 +2643,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "9464a6e45dfb43738c7874084ac2511e", "version_major": 2, "version_minor": 0 }, @@ -2393,7 +2657,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a5651d6107914f21bc97a9fd2c20b000", "version_major": 2, "version_minor": 0 }, @@ -2407,7 +2671,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b37a8d5ca7304c59a1664ab01623ea38", "version_major": 2, "version_minor": 0 }, @@ -2421,7 +2685,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "52f72ebf2fa746678a69ebd20a2ae421", "version_major": 2, "version_minor": 0 }, @@ -2435,7 +2699,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "574b08674760459b81784861b17f6075", "version_major": 2, "version_minor": 0 }, @@ -2449,7 +2713,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "9b79941ecf2d47629bb468627f87304d", "version_major": 2, "version_minor": 0 }, @@ -2463,7 +2727,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "afd5fd2289b14774abfecb664ae8f1f6", "version_major": 2, "version_minor": 0 }, @@ -2477,7 +2741,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1_Ch10/lib/python3.10/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:67: UserWarning: Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `pytorch_lightning` package, due to potential conflicts with other packages in the ML ecosystem. For this reason, `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard` or `tensorboardX` packages are found. Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default\n", " warning_cache.warn(\n", "\n", " | Name | Type | Params\n", @@ -2885,7 +3162,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "bfb904663981447bb712602e62891de1", "version_major": 2, "version_minor": 0 }, @@ -2899,7 +3176,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c932821add0e4296a5ff2122a94b6090", + "model_id": "e3364eae3d824a26aaf19ba7738f28b9", "version_major": 2, "version_minor": 0 }, @@ -2913,7 +3190,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e1dc3c094ca54b96ae09ea1c3f81cc96", "version_major": 2, "version_minor": 0 }, @@ -2927,7 +3204,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4a3e74d53cf140a29a4d1b01260bf530", "version_major": 2, "version_minor": 0 }, @@ -2941,7 +3218,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:33.746175Z", + "iopub.status.busy": "2023-08-22T06:38:33.746084Z", + "iopub.status.idle": "2023-08-22T06:38:35.260793Z", + "shell.execute_reply": "2023-08-22T06:38:35.260496Z" + } + }, "outputs": [ { "name": "stdout", @@ -3485,7 +3768,14 @@ "cell_type": "code", "execution_count": 50, "id": "2b613ecc", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:35.262479Z", + "iopub.status.busy": "2023-08-22T06:38:35.262391Z", + "iopub.status.idle": "2023-08-22T06:38:36.005488Z", + "shell.execute_reply": "2023-08-22T06:38:36.005166Z" + } + }, "outputs": [], "source": [ "transform = ToTensor()\n", @@ -3517,6 +3807,12 @@ "execution_count": 51, "id": "4b325cb4", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:36.007353Z", + "iopub.status.busy": "2023-08-22T06:38:36.007234Z", + "iopub.status.idle": "2023-08-22T06:38:36.010064Z", + "shell.execute_reply": "2023-08-22T06:38:36.009819Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -3541,6 +3837,12 @@ "execution_count": 52, "id": "cb3d00cb", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:36.011610Z", + "iopub.status.busy": "2023-08-22T06:38:36.011502Z", + "iopub.status.idle": "2023-08-22T06:38:38.616192Z", + "shell.execute_reply": "2023-08-22T06:38:38.615836Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -3580,6 +3882,12 @@ "execution_count": 53, "id": "60d09656", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:38.618165Z", + "iopub.status.busy": "2023-08-22T06:38:38.618040Z", + "iopub.status.idle": "2023-08-22T06:38:38.959064Z", + "shell.execute_reply": "2023-08-22T06:38:38.950625Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -3629,7 +3937,14 @@ "cell_type": "code", "execution_count": 54, "id": "f823da11", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:38.970097Z", + "iopub.status.busy": "2023-08-22T06:38:38.969929Z", + "iopub.status.idle": "2023-08-22T06:38:38.990599Z", + "shell.execute_reply": "2023-08-22T06:38:38.982099Z" + } + }, "outputs": [], "source": [ "class BuildingBlock(nn.Module):\n", @@ -3674,7 +3989,14 @@ "cell_type": "code", "execution_count": 55, "id": "1a172f7e", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:39.009337Z", + "iopub.status.busy": "2023-08-22T06:38:39.007564Z", + "iopub.status.idle": "2023-08-22T06:38:39.027768Z", + "shell.execute_reply": "2023-08-22T06:38:39.017688Z" + } + }, "outputs": [], "source": [ "class CIFARModel(nn.Module):\n", @@ -3711,6 +4033,12 @@ "execution_count": 56, "id": "651e62b4", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:39.041161Z", + "iopub.status.busy": "2023-08-22T06:38:39.040974Z", + "iopub.status.idle": "2023-08-22T06:38:39.147687Z", + "shell.execute_reply": "2023-08-22T06:38:39.147402Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -3747,7 +4075,7 @@ "Total params: 964,516\n", "Trainable params: 964,516\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.GIGABYTES): 2.01\n", + "Total mult-adds (G): 2.01\n", "===================================================================================================================\n", "Input size (MB): 1.57\n", "Forward/backward pass size (MB): 63.54\n", @@ -3807,7 +4135,14 @@ "cell_type": "code", "execution_count": 57, "id": "63f2650e", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:39.149388Z", + "iopub.status.busy": "2023-08-22T06:38:39.149267Z", + "iopub.status.idle": "2023-08-22T06:38:39.152471Z", + "shell.execute_reply": "2023-08-22T06:38:39.152156Z" + } + }, "outputs": [], "source": [ "cifar_optimizer = RMSprop(cifar_model.parameters(), lr=0.001)\n", @@ -3821,7 +4156,14 @@ "cell_type": "code", "execution_count": 58, "id": "a3e4bc28", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:38:39.153978Z", + "iopub.status.busy": "2023-08-22T06:38:39.153895Z", + "iopub.status.idle": "2023-08-22T06:41:13.243974Z", + "shell.execute_reply": "2023-08-22T06:41:13.243600Z" + } + }, "outputs": [ { "name": "stderr", @@ -3846,7 +4188,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "cf75ac2267f9488babf1c88067185953", "version_major": 2, "version_minor": 0 }, @@ -3860,7 +4202,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "40c811fa26da4690a95838e6ab0a8a98", + "model_id": "30da5d15249f473bb2e55004a4fbc6fc", "version_major": 2, "version_minor": 0 }, @@ -3874,7 +4216,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "75f26bea217748b1b0bfb0b97b06be25", "version_major": 2, "version_minor": 0 }, @@ -3888,7 +4230,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "abca09d01792423dbe50d4e71ea8bb2b", "version_major": 2, "version_minor": 0 }, @@ -3902,7 +4244,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "063695dad311441ebcfa6408148a54f2", "version_major": 2, "version_minor": 0 }, @@ -3916,7 +4258,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e0b1014a1bf24b4aa0a0062a215ecf06", "version_major": 2, "version_minor": 0 }, @@ -3930,7 +4272,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c06e825534814c1f8942b2fd0e719833", "version_major": 2, "version_minor": 0 }, @@ -3944,7 +4286,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4d3a2c2b34ce4cdba5387b4066c33bc1", "version_major": 2, "version_minor": 0 }, @@ -3958,7 +4300,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ca1c1a95c02f46588c9603928ad2c8eb", "version_major": 2, "version_minor": 0 }, @@ -3972,7 +4314,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "242fa898b94a40579e6a9331a5039240", "version_major": 2, "version_minor": 0 }, @@ -3986,7 +4328,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "7ad231ef819943fea0f68783c6e0ed4d", "version_major": 2, "version_minor": 0 }, @@ -4000,7 +4342,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "9b786b6275fd4693b006ef6e529e3227", "version_major": 2, "version_minor": 0 }, @@ -4014,7 +4356,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "5e42a316520f44ada04f9ce2978daa8a", "version_major": 2, "version_minor": 0 }, @@ -4028,7 +4370,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e9e3bd085ffd4dd68056e252d761edde", "version_major": 2, "version_minor": 0 }, @@ -4042,7 +4384,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4c7702499c474ebe887d17f110b136f7", "version_major": 2, "version_minor": 0 }, @@ -4056,7 +4398,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "3e38f9ac5d644c8b914fcda42d71fd30", "version_major": 2, "version_minor": 0 }, @@ -4070,7 +4412,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "12159193294842879e2abf2a6a57542c", "version_major": 2, "version_minor": 0 }, @@ -4084,7 +4426,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "d71292277b484c9ebcf31c730a7aece1", "version_major": 2, "version_minor": 0 }, @@ -4098,7 +4440,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "0016c30eadbe49ababf5b92c7fcf2f2b", "version_major": 2, "version_minor": 0 }, @@ -4112,7 +4454,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "feef8645a1134646b9ecde5310876ae1", "version_major": 2, "version_minor": 0 }, @@ -4126,7 +4468,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e30a991ac871447e98466cea30cc1e9b", "version_major": 2, "version_minor": 0 }, @@ -4140,7 +4482,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2ecaf65a04ee4b0698d666dcfdad463a", "version_major": 2, "version_minor": 0 }, @@ -4154,7 +4496,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8ca015472e6e49d5bf04f6eb6c147da4", "version_major": 2, "version_minor": 0 }, @@ -4168,7 +4510,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "7c265e3e36c94d0196236e5ef3aa587f", "version_major": 2, "version_minor": 0 }, @@ -4182,7 +4524,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "161a3af371ca4d60a28dcafe05d27e64", "version_major": 2, "version_minor": 0 }, @@ -4196,7 +4538,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e928c858bece4168a70610230c811c85", "version_major": 2, "version_minor": 0 }, @@ -4210,7 +4552,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2f8a344b80b14c0bbeca2fbafc3c7b8c", "version_major": 2, "version_minor": 0 }, @@ -4224,7 +4566,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "0a46cdb4c1b3476f9a6805a44088fed3", "version_major": 2, "version_minor": 0 }, @@ -4238,7 +4580,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "150df772fdeb468c8ae3dd482aba37d4", "version_major": 2, "version_minor": 0 }, @@ -4252,7 +4594,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "0d23b1967cfb439eaf23fd1c7d80aa58", "version_major": 2, "version_minor": 0 }, @@ -4266,7 +4608,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"model_id": "", + "model_id": "8561f251621b4b4bb80996645ee21113", "version_major": 2, "version_minor": 0 }, @@ -4491,7 +4838,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6409051044c94ad9af785a42df78d36e", + "model_id": "6ec66d48c6cb4c3d946961e005a8a479", "version_major": 2, "version_minor": 0 }, @@ -4506,14 +4853,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/torchmetrics/functional/classification/accuracy.py:77: UserWarning: MPS: no support for int64 reduction ops, casting it to int32 (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/ReduceOps.mm:144.)\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1_Ch10/lib/python3.10/site-packages/torchmetrics/functional/classification/accuracy.py:77: UserWarning: MPS: no support for int64 reduction ops, casting it to int32 (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/ReduceOps.mm:144.)\n", " tp = tp.sum(dim=0 if multidim_average == \"global\" else 1)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4d4700f8a59d48909fab4b18101147f7", "version_major": 2, "version_minor": 0 }, @@ -4527,7 +4874,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "3818f316eaca4ba495994364785ace29", "version_major": 2, "version_minor": 0 }, @@ -4541,7 +4888,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "733bcce394364359a4f1377471a556f3", "version_major": 2, "version_minor": 0 }, @@ -4555,7 +4902,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "741fbb3b9bb34571acfbe63d2cfc83b1", "version_major": 2, "version_minor": 0 }, @@ -4569,7 +4916,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "058f545200134cddb98ab49116a4b5b6", "version_major": 2, "version_minor": 0 }, @@ -4583,7 +4930,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2ef3ac0704564c54a5f010a467cb17b8", "version_major": 2, "version_minor": 0 }, @@ -4597,7 +4944,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6813b7f3eeab473ea3232bcb1a8b805e", "version_major": 2, "version_minor": 0 }, @@ -4611,7 +4958,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8fd851ce512b410b8a7c90b1ca2d4d88", "version_major": 2, "version_minor": 0 }, @@ -4625,7 +4972,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b07cf4aa47a84e4186a0184c774f1b62", "version_major": 2, "version_minor": 0 }, @@ -4639,7 +4986,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "74c3c3d036394b729679bb50be07979f", "version_major": 2, "version_minor": 0 }, @@ -4653,7 +5000,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4d9b17ce0c264604ad78cca0b4a95c83", "version_major": 2, "version_minor": 0 }, @@ -4667,7 +5014,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c169f02b4204490bb077558716d3774e", "version_major": 2, "version_minor": 0 }, @@ -4681,7 +5028,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "18a31aba978d4a8692111fb6c55fe85d", "version_major": 2, "version_minor": 0 }, @@ -4695,7 +5042,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c520605694ca49158bca1679e5987432", "version_major": 2, "version_minor": 0 }, @@ -4709,7 +5056,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "59894643e27a46a091c3c42ffd1e9797", "version_major": 2, "version_minor": 0 }, @@ -4723,7 +5070,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "5adba0c8771a46e9a4b64c5492134377", "version_major": 2, "version_minor": 0 }, @@ -4737,7 +5084,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "05cc7d17519247d4bed8d0260fd8c9c6", "version_major": 2, "version_minor": 0 }, @@ -4751,7 +5098,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "48808854ac234c8ca63b5e5b273f17bd", "version_major": 2, "version_minor": 0 }, @@ -4765,7 +5112,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "92cf213e529d4e34be6d8473a8ca6b23", "version_major": 2, "version_minor": 0 }, @@ -4779,7 +5126,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ec82fcb270004491a95123102e13a852", "version_major": 2, "version_minor": 0 }, @@ -4793,7 +5140,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "5abf5e8af169412a9ceef746437ccaf4", "version_major": 2, "version_minor": 0 }, @@ -4807,7 +5154,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "978f680372c846dabc500b9ccb9b80d8", "version_major": 2, "version_minor": 0 }, @@ -4821,7 +5168,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ac9a9c30854f4607a35ddb6623a312b6", "version_major": 2, "version_minor": 0 }, @@ -4835,7 +5182,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ad5df9b2fa754520af1210fe3e8e8406", "version_major": 2, "version_minor": 0 }, @@ -4849,7 +5196,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "27ff88a097934fecb6d5897713435267", "version_major": 2, "version_minor": 0 }, @@ -4863,7 +5210,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "243e06349f03454cbcab5ecd2d67f896", "version_major": 2, "version_minor": 0 }, @@ -4877,7 +5224,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "9443d9fd5d7b45649a37e5cc1f52c58d", "version_major": 2, "version_minor": 0 }, @@ -4891,7 +5238,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c531fb2f7d5244ad8d0c0e4a4ee028c7", "version_major": 2, "version_minor": 0 }, @@ -4905,7 +5252,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b5460433203542fea838b387894252c0", "version_major": 2, "version_minor": 0 }, @@ -4919,7 +5266,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c7c5e5f98571429b8dd82815442cd626", "version_major": 2, "version_minor": 0 }, @@ -4940,7 +5287,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4f37d3b614314b6fbf9dfb3df1775948", + "model_id": "486106ba7b134b3682fc506c03ebce5e", "version_major": 2, "version_minor": 0 }, @@ -5003,6 +5350,12 @@ "execution_count": 62, "id": "a71c9acb", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:01.469991Z", + "iopub.status.busy": "2023-08-22T06:44:01.469875Z", + "iopub.status.idle": "2023-08-22T06:44:01.935872Z", + "shell.execute_reply": "2023-08-22T06:44:01.935582Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -5042,6 +5395,12 @@ "execution_count": 63, "id": "4f890244", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:01.937487Z", + "iopub.status.busy": "2023-08-22T06:44:01.937384Z", + "iopub.status.idle": "2023-08-22T06:44:02.437287Z", + "shell.execute_reply": "2023-08-22T06:44:02.436974Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -5230,7 +5589,7 @@ "Total params: 25,557,032\n", "Trainable params: 25,557,032\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.GIGABYTES): 24.54\n", + "Total mult-adds (G): 24.54\n", "===================================================================================================================\n", "Input size (MB): 3.61\n", "Forward/backward pass size (MB): 1066.99\n", @@ -5266,6 +5625,12 @@ "execution_count": 64, "id": "c4be9922", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.438850Z", + "iopub.status.busy": "2023-08-22T06:44:02.438741Z", + "iopub.status.idle": "2023-08-22T06:44:02.441925Z", + "shell.execute_reply": "2023-08-22T06:44:02.441612Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -5475,7 +5840,14 @@ "cell_type": "code", "execution_count": 65, "id": "2dc63d85", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.443425Z", + "iopub.status.busy": "2023-08-22T06:44:02.443344Z", + "iopub.status.idle": "2023-08-22T06:44:02.567717Z", + "shell.execute_reply": "2023-08-22T06:44:02.567412Z" + } + }, "outputs": [], "source": [ "img_preds = resnet_model(imgs)\n" @@ -5496,7 +5868,14 @@ "cell_type": "code", "execution_count": 66, "id": "711d5ba7", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.569455Z", + "iopub.status.busy": "2023-08-22T06:44:02.569371Z", + "iopub.status.idle": "2023-08-22T06:44:02.571608Z", + "shell.execute_reply": "2023-08-22T06:44:02.571356Z" + } + }, "outputs": [], "source": [ "img_probs = np.exp(np.asarray(img_preds.detach()))\n", @@ -5515,7 +5894,14 @@ "cell_type": "code", "execution_count": 67, "id": "b22f70d8", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.573175Z", + "iopub.status.busy": "2023-08-22T06:44:02.573082Z", + "iopub.status.idle": "2023-08-22T06:44:02.580482Z", + "shell.execute_reply": "2023-08-22T06:44:02.580237Z" + } + }, "outputs": [], "source": [ "labs = json.load(open('imagenet_class_index.json'))\n", @@ -5541,6 +5927,12 @@ "execution_count": 68, "id": "b19c6bd1", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.581982Z", + "iopub.status.busy": "2023-08-22T06:44:02.581889Z", + "iopub.status.idle": "2023-08-22T06:44:02.593476Z", + "shell.execute_reply": "2023-08-22T06:44:02.593210Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -5607,6 +5999,12 @@ "execution_count": 69, "id": "ba80b615", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.594912Z", + "iopub.status.busy": "2023-08-22T06:44:02.594816Z", + "iopub.status.idle": "2023-08-22T06:44:02.596527Z", + "shell.execute_reply": "2023-08-22T06:44:02.596344Z" + }, "lines_to_next_cell": 2 }, "outputs": [], @@ -5651,6 +6049,12 @@ "execution_count": 70, "id": "ba6d2d2c", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.597905Z", + "iopub.status.busy": "2023-08-22T06:44:02.597817Z", + "iopub.status.idle": "2023-08-22T06:44:02.626372Z", + "shell.execute_reply": "2023-08-22T06:44:02.626104Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -5695,7 +6099,14 @@ "cell_type": "code", "execution_count": 71, "id": "93bda908", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.627866Z", + "iopub.status.busy": "2023-08-22T06:44:02.627766Z", + "iopub.status.idle": "2023-08-22T06:44:02.638183Z", + "shell.execute_reply": "2023-08-22T06:44:02.637892Z" + } + }, "outputs": [ { "data": { @@ -5730,6 +6141,12 @@ "execution_count": 72, "id": "40943b7d", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:02.639670Z", + "iopub.status.busy": "2023-08-22T06:44:02.639577Z", + "iopub.status.idle": "2023-08-22T06:44:03.265220Z", + "shell.execute_reply": "2023-08-22T06:44:03.264917Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -5757,6 +6174,12 @@ "execution_count": 73, "id": "2117fd9f", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:03.267054Z", + "iopub.status.busy": "2023-08-22T06:44:03.266963Z", + "iopub.status.idle": "2023-08-22T06:44:03.269380Z", + "shell.execute_reply": "2023-08-22T06:44:03.269155Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -5793,7 +6216,14 @@ "cell_type": "code", "execution_count": 74, "id": "66d0b710", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:03.270876Z", + "iopub.status.busy": "2023-08-22T06:44:03.270774Z", + "iopub.status.idle": "2023-08-22T06:44:04.097412Z", + "shell.execute_reply": "2023-08-22T06:44:04.097126Z" + } + }, "outputs": [ { "data": { @@ -5811,7 +6241,7 @@ "Total params: 160,353\n", "Trainable params: 160,353\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.GIGABYTES): 4.01\n", + "Total mult-adds (G): 4.01\n", "===================================================================================================================\n", "Input size (MB): 1000.30\n", "Forward/backward pass size (MB): 6.60\n", @@ -5855,7 +6285,14 @@ "cell_type": "code", "execution_count": 75, "id": "9df8b4cf", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:04.101984Z", + "iopub.status.busy": "2023-08-22T06:44:04.101529Z", + "iopub.status.idle": "2023-08-22T06:44:04.111524Z", + "shell.execute_reply": "2023-08-22T06:44:04.110929Z" + } + }, "outputs": [], "source": [ "imdb_optimizer = RMSprop(imdb_model.parameters(), lr=0.001)\n", @@ -5878,7 +6315,14 @@ "cell_type": "code", "execution_count": 76, "id": "73684c66", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:04.113582Z", + "iopub.status.busy": "2023-08-22T06:44:04.113437Z", + "iopub.status.idle": "2023-08-22T06:44:22.590794Z", + "shell.execute_reply": "2023-08-22T06:44:22.590448Z" + } + }, "outputs": [ { "name": "stderr", @@ -5903,7 +6347,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "795333e5d7b84fc6812fcf3dd6391bfa", "version_major": 2, "version_minor": 0 }, @@ -5918,14 +6362,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:280: PossibleUserWarning: The number of training batches (45) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n", + "/Users/jonathantaylor/anaconda3/envs/isolated_env_1eb44da1_Ch10/lib/python3.10/site-packages/pytorch_lightning/loops/fit_loop.py:280: PossibleUserWarning: The number of training batches (45) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n", " rank_zero_warn(\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "253cf3e077d845569cdc459ef74902b6", + "model_id": "7c1ce82c29a644f68f5706783e08927a", "version_major": 2, "version_minor": 0 }, @@ -5939,7 +6383,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b1ac59bc49094a708bfa29f4fc194a71", "version_major": 2, "version_minor": 0 }, @@ -5953,7 +6397,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "21a870683e2a4e0ebb2b86c8c9afeb53", "version_major": 2, "version_minor": 0 }, @@ -5967,7 +6411,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8bae27914733459abdb5e8df79747137", "version_major": 2, "version_minor": 0 }, @@ -5981,7 +6425,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8804e3a20d1c49958518a664bd63f369", "version_major": 2, "version_minor": 0 }, @@ -5995,7 +6439,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "06686ccf9eea46a498c78fc6ed739fc2", "version_major": 2, "version_minor": 0 }, @@ -6009,7 +6453,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "4054f655d9a048e380f86adadf5b1312", "version_major": 2, "version_minor": 0 }, @@ -6023,7 +6467,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "f5f469b4c14a4a6687acd450b5c0ad69", "version_major": 2, "version_minor": 0 }, @@ -6037,7 +6481,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "feccfd4b4d3b4bc8835c5e0e332f18ff", "version_major": 2, "version_minor": 0 }, @@ -6051,7 +6495,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "db31f3721f9d4bb68940c4b68363ae91", "version_major": 2, "version_minor": 0 }, @@ -6065,7 +6509,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "3f3cfeef6c994126bb25ef544e10d3e2", "version_major": 2, "version_minor": 0 }, @@ -6079,7 +6523,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "77450f9684cd42ac9ebc992dd86590b7", "version_major": 2, "version_minor": 0 }, @@ -6093,7 +6537,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "0d41009181074ffcbc2b81fd23a5e486", "version_major": 2, "version_minor": 0 }, @@ -6107,7 +6551,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "86ad33abbff742d3a66014271d575da4", "version_major": 2, "version_minor": 0 }, @@ -6121,7 +6565,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "170aa9e0a58c449f97cc5d210cba04a9", "version_major": 2, "version_minor": 0 }, @@ -6135,7 +6579,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6357463ea1464043b3aaa481d08ec4dc", "version_major": 2, "version_minor": 0 }, @@ -6149,7 +6593,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "c67de6d754454a28a4eb9da14cfb9b45", "version_major": 2, "version_minor": 0 }, @@ -6163,7 +6607,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "226a8c4a25194a5597a56915a9a203e6", "version_major": 2, "version_minor": 0 }, @@ -6177,7 +6621,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "ab01bdbc450a426b8766f783bb71eb17", "version_major": 2, "version_minor": 0 }, @@ -6191,7 +6635,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2e7f5f09bce94cdd808251b783ff7195", "version_major": 2, "version_minor": 0 }, @@ -6205,7 +6649,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "077790461d6a43db8c785be6c6f2f71b", "version_major": 2, "version_minor": 0 }, @@ -6219,7 +6663,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "7782347a868a4cb09ad084e0593fc921", "version_major": 2, "version_minor": 0 }, @@ -6233,7 +6677,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "46a12e5ee12547f5864399e6f3cdd08b", "version_major": 2, "version_minor": 0 }, @@ -6247,7 +6691,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6cc156f0ca724500b25ebd9e8f9e11df", "version_major": 2, "version_minor": 0 }, @@ -6261,7 +6705,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "02c4f52ca3784311886f0616648ece3f", "version_major": 2, "version_minor": 0 }, @@ -6275,7 +6719,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "9ef5b02f482344818b2aeb04cc8ff5bf", "version_major": 2, "version_minor": 0 }, @@ -6289,7 +6733,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "2ed0de87ff334b7396d54733b8cb942c", "version_major": 2, "version_minor": 0 }, @@ -6303,7 +6747,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "710efb8aace342a48ef6148920857667", "version_major": 2, "version_minor": 0 }, @@ -6317,7 +6761,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "491665fa6ec546cc87dfe5f3ad1858f5", "version_major": 2, "version_minor": 0 }, @@ -6331,7 +6775,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:24.382775Z", + "iopub.status.busy": "2023-08-22T06:44:24.382660Z", + "iopub.status.idle": "2023-08-22T06:44:24.491042Z", + "shell.execute_reply": "2023-08-22T06:44:24.490723Z" + } + }, "outputs": [], "source": [ "((X_train, Y_train),\n", @@ -6486,6 +6930,12 @@ "execution_count": 79, "id": "e2a88e57", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:24.492855Z", + "iopub.status.busy": "2023-08-22T06:44:24.492752Z", + "iopub.status.idle": "2023-08-22T06:44:24.497193Z", + "shell.execute_reply": "2023-08-22T06:44:24.496916Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -6511,6 +6961,12 @@ "execution_count": 80, "id": "9a3cf7a3", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:24.498888Z", + "iopub.status.busy": "2023-08-22T06:44:24.498790Z", + "iopub.status.idle": "2023-08-22T06:44:24.500775Z", + "shell.execute_reply": "2023-08-22T06:44:24.500516Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -6534,7 +6990,14 @@ "cell_type": "code", "execution_count": 81, "id": "b46f02c2", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:24.502208Z", + "iopub.status.busy": "2023-08-22T06:44:24.502114Z", + "iopub.status.idle": "2023-08-22T06:44:43.491232Z", + "shell.execute_reply": "2023-08-22T06:44:43.490911Z" + } + }, "outputs": [], "source": [ "coefs = []\n", @@ -6561,6 +7024,12 @@ "execution_count": 82, "id": "e5fb6afa", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.492990Z", + "iopub.status.busy": "2023-08-22T06:44:43.492881Z", + "iopub.status.idle": "2023-08-22T06:44:43.495136Z", + "shell.execute_reply": "2023-08-22T06:44:43.494898Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -6583,6 +7052,12 @@ "execution_count": 83, "id": "cad28f1a", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.496615Z", + "iopub.status.busy": "2023-08-22T06:44:43.496512Z", + "iopub.status.idle": "2023-08-22T06:44:43.817649Z", + "shell.execute_reply": "2023-08-22T06:44:43.804167Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -6626,6 +7101,12 @@ "execution_count": 84, "id": "a66ecdd8", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.829522Z", + "iopub.status.busy": "2023-08-22T06:44:43.829394Z", + "iopub.status.idle": "2023-08-22T06:44:43.970259Z", + "shell.execute_reply": "2023-08-22T06:44:43.969880Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -6673,6 +7154,12 @@ "execution_count": 85, "id": "62440c1c", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.972104Z", + "iopub.status.busy": "2023-08-22T06:44:43.971981Z", + "iopub.status.idle": "2023-08-22T06:44:43.973750Z", + "shell.execute_reply": "2023-08-22T06:44:43.973468Z" + }, "lines_to_next_cell": 2 }, "outputs": [], @@ -6718,7 +7205,14 @@ "cell_type": "code", "execution_count": 86, "id": "c73d6e28", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.975482Z", + "iopub.status.busy": "2023-08-22T06:44:43.975361Z", + "iopub.status.idle": "2023-08-22T06:44:43.977735Z", + "shell.execute_reply": "2023-08-22T06:44:43.977461Z" + } + }, "outputs": [], "source": [ "imdb_seq_dm = SimpleDataModule(imdb_seq_train,\n", @@ -6762,6 +7256,12 @@ "execution_count": 87, "id": "cc9bbd00", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.979333Z", + "iopub.status.busy": "2023-08-22T06:44:43.979219Z", + "iopub.status.idle": "2023-08-22T06:44:43.981720Z", + "shell.execute_reply": "2023-08-22T06:44:43.981436Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -6792,7 +7292,14 @@ "cell_type": "code", "execution_count": 88, "id": "5c9ffb46", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:43.983706Z", + "iopub.status.busy": "2023-08-22T06:44:43.983605Z", + "iopub.status.idle": "2023-08-22T06:44:44.006133Z", + "shell.execute_reply": "2023-08-22T06:44:44.005857Z" + } + }, "outputs": [ { "data": { @@ -6808,7 +7315,7 @@ "Total params: 328,577\n", "Trainable params: 328,577\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.MEGABYTES): 45.44\n", + "Total mult-adds (M): 45.44\n", "===================================================================================================================\n", "Input size (MB): 50.00\n", "Forward/backward pass size (MB): 2.56\n", @@ -6844,7 +7351,14 @@ "cell_type": "code", "execution_count": 89, "id": "a2d6ddfd", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:44.007842Z", + "iopub.status.busy": "2023-08-22T06:44:44.007718Z", + "iopub.status.idle": "2023-08-22T06:44:44.010586Z", + "shell.execute_reply": "2023-08-22T06:44:44.010323Z" + } + }, "outputs": [], "source": [ "lstm_module = SimpleModule.binary_classification(lstm_model)\n", @@ -6856,6 +7370,12 @@ "execution_count": 90, "id": "1d76f970", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:44:44.012129Z", + "iopub.status.busy": "2023-08-22T06:44:44.012007Z", + "iopub.status.idle": "2023-08-22T06:57:52.592058Z", + "shell.execute_reply": "2023-08-22T06:57:52.591679Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -6882,7 +7402,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "378b19c7eac744308f7e66510ed91e53", "version_major": 2, "version_minor": 0 }, @@ -6896,7 +7416,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e24a4171456b412db47d6577cb336c37", + "model_id": "ef5ef897fb0f445d8bdbb9603ab9fe1f", "version_major": 2, "version_minor": 0 }, @@ -6910,7 +7430,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a366613bbed148f99faf7c3048fd5342", "version_major": 2, "version_minor": 0 }, @@ -6924,7 +7444,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "33c8cd8f47a44e5a86e58f83612915ab", "version_major": 2, "version_minor": 0 }, @@ -6938,7 +7458,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "44ba1553a3f54642b05ce7524df82025", "version_major": 2, "version_minor": 0 }, @@ -6952,7 +7472,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "fe4ad23d277b45bd9ac5e6b01e8a755a", "version_major": 2, "version_minor": 0 }, @@ -6966,7 +7486,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "5d76d21f617146b19033d03068811bae", "version_major": 2, "version_minor": 0 }, @@ -6980,7 +7500,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "1a61a4d5b3f64c85b9d36656ab359beb", "version_major": 2, "version_minor": 0 }, @@ -6994,7 +7514,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e25cb2f8f14c4b6099c1a1b37e89ed54", "version_major": 2, "version_minor": 0 }, @@ -7008,7 +7528,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a74e862dfa64467ca538e1decb34ebd6", "version_major": 2, "version_minor": 0 }, @@ -7022,7 +7542,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6d3dd1f4233a4e779585e1be6aee8943", "version_major": 2, "version_minor": 0 }, @@ -7036,7 +7556,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "6c69d1606f5e43d399996acdd4b275fe", "version_major": 2, "version_minor": 0 }, @@ -7050,7 +7570,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "652b9712efa04ab2a0444464fb7aef43", "version_major": 2, "version_minor": 0 }, @@ -7064,7 +7584,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "8a69f0865eec43b5bab4d01c62ccc2dc", "version_major": 2, "version_minor": 0 }, @@ -7078,7 +7598,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "56fd72140fdf48fe87011e828715d038", "version_major": 2, "version_minor": 0 }, @@ -7092,7 +7612,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "aaad6e2fd6ff44aa9e7842830f2c31c5", "version_major": 2, "version_minor": 0 }, @@ -7106,7 +7626,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "3eee2abff98b4e1080d1ade699034ec0", "version_major": 2, "version_minor": 0 }, @@ -7120,7 +7640,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "1d18c86360cd4e32b69f20bb667f41ad", "version_major": 2, "version_minor": 0 }, @@ -7134,7 +7654,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "e100cb13de18446f85a7d9864b04fbbf", "version_major": 2, "version_minor": 0 }, @@ -7148,7 +7668,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "b22c18caa3c945ec9b5ea2427c8b76ad", "version_major": 2, "version_minor": 0 }, @@ -7162,7 +7682,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "a3282157e73a4b6ba710cd530f2911e6", "version_major": 2, "version_minor": 0 }, @@ -7176,7 +7696,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "56a98588414e4d21a98f337a9121e943", "version_major": 2, "version_minor": 0 }, @@ -7217,12 +7737,19 @@ "cell_type": "code", "execution_count": 91, "id": "d8a60d35", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:52.595337Z", + "iopub.status.busy": "2023-08-22T06:57:52.595214Z", + "iopub.status.idle": "2023-08-22T06:57:55.788029Z", + "shell.execute_reply": "2023-08-22T06:57:55.787703Z" + } + }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4e512ef8a7d348eea7f423a9ed96c86e", + "model_id": "295ea7acd6904c2bac76f95a99e0e77e", "version_major": 2, "version_minor": 0 }, @@ -7234,34 +7761,21 @@ "output_type": "display_data" }, { - "data": { - "text/html": [ - "
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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", + " Test metric DataLoader 0\n", + "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", + " test_accuracy 0.8549200296401978\n", + " test_loss 0.7031683325767517\n", + "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" + ] }, { "data": { "text/plain": [ - "[{'test_loss': 0.7677657604217529, 'test_accuracy': 0.8480799794197083}]" + "[{'test_loss': 0.7031683325767517, 'test_accuracy': 0.8549200296401978}]" ] }, "execution_count": 91, @@ -7286,6 +7800,12 @@ "execution_count": 92, "id": "65d7276c", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:55.789720Z", + "iopub.status.busy": "2023-08-22T06:57:55.789606Z", + "iopub.status.idle": "2023-08-22T06:57:55.884354Z", + "shell.execute_reply": "2023-08-22T06:57:55.882420Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -7301,7 +7821,7 @@ }, { "data": { - "image/png": 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ypXr37q2dO3fqtttuU+fOnXXvvfdq8uTJ+vjjj7Vhwwa98cYbkqSoel6HiooKpaamKjk5WR988IEOHjyoW2+9VTNnzvQJWXl5eYqNjVVeXp727NmjyZMna+jQobrtttvO+HwCld0rkPpzKG1TVydlZVMAp2W1MaWlpZYkq7S0tM5tx44dsz755BPr2LFj/2ksL7esmvjQ8pfy8kY/r127dlmSrLy8PG9bSkqKdeONN9a7/Y9+9CPrv//7v73XL7/8ciszM9N7vU+fPtaTTz5pWZZlvf7661a7du2swsJC7+2vvfaaJclat25dgzU99thj1rBhw7zXFy1aZA0ZMqTOdifv57nnnrO6du1qlZ/03F955RUrJCTEKi4utizLsjIyMqw+ffpYJ06c8G7z05/+1Jo8eXKDtdT73gaQl156yXK5XJYkn4vL5bJcLpf10ksv+b3PVatW1dlffZdVq1Y58IwABKLTfYc2BcMxZxIRUdMj0ZjLq682bp+vvtq4/fkxJ+O8887TpZdequeff16StGfPHhUUFOiWW26Rx+PRww8/rEGDBqlbt27q1KmTXn/9de3bt69R+961a5cSEhLUu3dvb1tycnKd7dasWaPLLrtMMTEx6tSpkxYsWNDoxzj5sYYMGaKOJ/UAXXbZZaqurtbu3bu9bRdccIHPxMbY2FgdPHjQr8cKFE4Nm3AoLQDTCCFn4nLVDIk05nL11VJ8fM19GtpXQkLNdo3ZX0P7acAtt9yil156Sd9++61WrFihs88+W5dffrkee+wxLV26VHPnzlVeXp62b9+u1NRUVVVV2fAC1di8ebNuuOEGjRs3Tn/729/04Ycfav78+bY+xsnat2/vc93lcqm6utqRxzLNqRVIOZQWgGmEEDu53dL3hybWCRC117OyarZzwHXXXaeQkBCtWrVKf/zjH/Vf//VfcrlceueddzRhwgTdeOONGjJkiPr166d//vOfjd7vwIEDtX//fp8VLt977z2fbd5991316dNH8+fP1/Dhw9W/f3999dVXPtuEhoae8df6wIEDtWPHDlVUVHjb3nnnHYWEhGjAgAGNrjmYOLUCKYfSAjCNEGK3tDQpO1s65dBExcfXtDt4ZECnTp00efJkzZs3T0VFRbr55pslSf3799fGjRv17rvvateuXfrZz36mkpKSRu93zJgxOvfcc5WRkaEdO3aooKBA8+fP99mmf//+2rdvn1588UV9/vnn+s1vfqN169b5bJOYmKi9e/dq+/btOnTokCorK+s81g033KAOHTooIyNDH3/8sfLy8jRr1izddNNNio6O9v9FCQJODptwKC0AkwghTkhLk778UsrLk1atqvl3715HA0itW265Rf/+97+VmprqncOxYMECXXzxxUpNTdWoUaMUExOjiRMnNnqfISEhWrdunY4dO6aRI0fq1ltv1S9/+UufbX7yk5/o7rvv1syZMzV06FC9++67Wrhwoc821157rcaOHavRo0erZ8+e9R4mHBERoddff12HDx/WiBEjlJ6eriuvvFJPP/20/y9GkHB62IRDaQGY4rLqm+0WxMrKyhQVFaXS0lJFRkb63Pbdd99p79696tu3rzp06GCoQjgh0N/b2kXFJPlMUK0NJvRaAGgJp/sObQp6QoAAwLAJgGDEYmVAgEhLS9OECRNUUFCgoqIixcbGKiUlhYmjAAIWIQQIIKxACiCYMBwDAACMIITUo43N1W0TeE8BoPVhOOYktatwHj16VOHh4YargZ2OHj0qqe5Kq07xeDzM3QCAMyCEnMTtdqtLly7ec5BEREQ0uDYDAoNlWTp69KgOHjyoLl26tEgQsPtstwAQrAghp4iJiZGkoD0ZWlvVpUsX73vrpNr1PE4d/iksLFR6ejqH0wLASVisrAEej0fHjx9vwcrglPbt27dID4jH41FiYmKDJ5tzuVyKj4/X3r17GZoBEJDsXqyMnpAGuN1uvijgF3/OdsthtgDA0TGAbZw62y0ABCtCCGATJ892CwDBiBAC2MTps90CQLAhhAA2cbvdWrp0qSTVCSK117OysphrBADfI4SgzfJ4PMrPz9fq1auVn58vj8fT7H1ytlsAaDwO0UWb5PSCYqyYCiAY2f0dSghBm9PQgmK1Qyb0WABA/ez+DmU4Bm2Kx+NRZmZmvSe0q22bPXu2LUMzAIDTI4SgTfFnQTEAgLMIIWhTWFAMAFoPQgjaFBYUA4DWgxCCNoUFxQCg9SCEoE1hQTEAaD0IIWhzWFAMAFoH1glBm8WCYgDgH7u/Q9vZUBPgKKfCgtvt1qhRo5pfIACgSQghaNWcXl4dAGAOc0LQatUur37q4mKFhYVKT09XTk6OocoAAHYghKBVYnl1AAh+hBC0SiyvDgDBjxCCVonl1QEg+BFC0CqxvDoABD9CCFolllcHgOBHCEGrxPLqABD8CCFotVheHQCCG8u2o9VjeXUAaB1Yth1tDsurA0BwYjgGAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhhPIQsW7ZMiYmJ6tChg5KSkrRly5YGtz1+/LgeeughnX322erQoYOGDBmiDRs2tGC1AADALkZDyJo1azRnzhwtWrRI27Zt05AhQ5SamqqDBw/Wu/2CBQv0u9/9Tk899ZQ++eQT3XHHHZo0aZI+/PDDFq4cAAA0l9HFypKSkjRixAg9/fTTkqTq6molJCRo1qxZuu++++ps37t3b82fP18zZszwtl177bUKDw/Xn/70p0Y9JouVOYdFxQAguNn9HWqsJ6Sqqkpbt27VmDFj/lNMSIjGjBmjzZs313ufyspKdejQwactPDxcb7/9doOPU1lZqbKyMp8L7JeTk6PExESNHj1aU6dO1ejRo5WYmKicnBzTpQEAWiljIeTQoUPyeDyKjo72aY+OjlZxcXG990lNTdUTTzyhzz77TNXV1dq4caNycnJUVFTU4OMsWbJEUVFR3ktCQoKtzwM1ASQ9PV0HDhzwaS8sLFR6ejpBBABQL+MTU/2xdOlS9e/fX+edd55CQ0M1c+ZMTZ8+XSEhDT+NefPmqbS01HvZv39/C1Yc/DwejzIzM1XfqF5t2+zZs+XxeFq6NABAK2cshPTo0UNut1slJSU+7SUlJYqJian3Pj179tT69etVUVGhr776Sp9++qk6deqkfv36Nfg4YWFhioyM9LnAPgUFBXV6QE5mWZb279+vgoKCFqwKABAIjIWQ0NBQDRs2TLm5ud626upq5ebmKjk5+bT37dChg+Li4nTixAm99NJLmjBhgtPlogGnGwprynYAgLbD6Fl058yZo4yMDA0fPlwjR45UVlaWKioqNH36dEnStGnTFBcXpyVLlkiS3n//fRUWFmro0KEqLCzUgw8+qOrqat17770mn0abFhsba+t2AIC2w2gImTx5sr755hs98MADKi4u1tChQ7VhwwbvZNV9+/b5zPf47rvvtGDBAn3xxRfq1KmTxo0bpxdeeEFdunQx9AyQkpKi+Ph4FRYW1jsvxOVyKT4+XikpKQaqAwC0ZkbXCTGBdULsV3t0jCSfIOJyuSRJ2dnZSktLM1IbAMA+QbNOCIJHWlqasrOzFRcX59MeHx9PAAEANIieENiGFVMBILjZ/R1qdE4Igovb7daoUaNMlwEACBAMxwAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwIh2pgtAy/N4PCooKFBRUZFiY2OVkpIit9ttuiwAQBtDCGljcnJylJmZqQMHDnjb4uPjtXTpUqWlpRmsDADQ1jAc04bk5OQoPT3dJ4BIUmFhodLT05WTk2OoMgBAW0QIaSM8Ho8yMzNlWVad22rbZs+eLY/H09KlAQDaKIZj2oiCgoI6PSAnsyxL+/fvV0FBgUaNGtVyhTWGxyMVFEhFRVJsrJSSIjGHxV5Ovca8dwBOgxDSRhQVFdm6XYvJyZEyM6WTA1R8vLR0qcQcFns49Rrz3gE4A4Zj2ojY2Fhbt2sROTlSerrvl5gkFRbWtDOHpfmceo157wA0gsuqb5JAECsrK1NUVJRKS0sVGRlpupwW4/F4lJiYqMLCwnrnhbhcLsXHx2vv3r2t43Bdj0dKTKz7JVbL5ar5Vb13L937TeXUa8x7BwQtu79D6QlpI9xut5YuXSqpJnCcrPZ6VlZW6wggUs08gtPMYZFlSfv312zXVB6PlJ8vrV5d829bm5Tr1GvcEu8dgKBACGlD0tLSlJ2drbi4OJ/2+Ph4ZWdnt651Qho7N6Wpc1hycmp+rY8eLU2dWvNvYmLbGiZw6jV2+r2TCJBAkGBiahuTlpamCRMmtP4VUxs7N6Upc1hq5yucOixVO18hO7ttTJx06jV28r2TmPAKBBHmhKB1qp1XUFhYNyxIzFewg9Ovsd37lRoOkLVDjG0lQAKGMCcEbYPbXfPLVvrPF0yt2utZWf5/iTFf4T+ceo2d2q/HU9MDUl+wqW2bPZuhGSCAEELQeqWl1fyyPWUOi+Ljm/6LtyXmK0iBM2fBidfYqf0SIIGgw5wQtG5padKECfatuun0fAUp8OYs2P0aO7XflgqQAFoMc0LQtjg5X0FizoKT8vNrjmI6k7w8qbWdeiAQseQ+6sGcEKA5nJqvIDFnwWkpKTUB8dT3rZbLJSUk1GyH5nHyEPZAGapEiyCEoO1xah4Ecxac5WSADGR2f6k7ueQ+6/PgFIQQtE1padKXX9Z03a9aVfPv3r3NGyphzoLznAqQgcruL3Une/M4nxDqwZwQwC4tMWeBcfoavA7OzD9y6v9h1ucJGswJAVorp+cs0JX9H253zZfglCk1/7a1Ly6neiyc6s1jqBINIITAPm19wpmTcxboysbJnPpSd+oQ9kAfqmzrf9scRAiBPfiVXsOJOQscdYNTOfWl7lRvXkusz+NUUOBvm6MIIWg+fqX7snvSK13ZOJVTX+pO9eYF6lAlf9scRwhpi+z8xcCv9PrZOWch0LuyA00gdL07+aXuRG9eIA5V8retRRBC2hq7fzHwK915LdGVjRqB0vXu9JopThzCHmhDlfxtaxGEkLbEiV8M/Ep3HiuFtgynu97t7mFxes0UJ45ACqShSv62tQhOYNdWnOkXg8tV84thwgT//tjwK915tb9609Nr3qeT38O2vFKonZz6fNRy6qSGTp180Em14cYOTgaFQP7bFkDr6NAT0lY49YuBX+ktg5VCneXkL2qne1ja8popTgaFlvjb5sT8o0AZUvweIaStcOoXA+fzaDlOjNOjhlOfDyY3OsvJoOD03zYnwkIAHs1DCGkrnPzFwK/0ltOWf/U6yanPB5MbndUSE3Sd+NvmRFgI0MDLuWPaitpzNxQW1v8/qR3nbgigcUjAh1Ofj9Wra37lnsmqVTXBEk1T35ybhISaAGLHjyA7/7Y5dR6dljh3lez/DmVialvREpMb7ZxwBrQkpz4fgTy5MZA4PUHXzr9t/vSO+fOYAXo0D8MxbQnDJkDDnPh8MHG75QTKUKVTYSFAAy89IW1NIB7SB7QUuz8fHF6NUzkVFmoD75mGFFtZ4GVOCAA4zek5CwgcTs7Pq53wKtUfeG3o8bb7O5ThGABwGodXo5aTR/QE4JA7PSEAALQ0J3vHHDxS0e7vUEIIAAAmBOCyBhyiCwBAMGBZA+aEAAAAMwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADAiHamC0DDPB6PCgoKVFRUpNjYWKWkpMjtdpsuCwAAWxBCWqmcnBxlZmbqwIED3rb4+HgtXbpUaWlpBisDAMAeDMe0Qjk5OUpPT/cJIJJUWFio9PR05eTkGKoMAAD7EEJaGY/Ho8zMTFmWpRBJl0u6/vt/XZYlSZo9e7Y8Ho/BKgEAaD5CSCtTUFCgAwcOaJKkLyXlS1r9/b9fSppoWdq/f78KCgpMlQgAgC2YE9LKFBUVaZKk7Hpui/u+Pf377QAACGT0hLQysb16aen3/33qm1N7Pev77QAACGT0hLQyKZJOdxBuiKSzVNMrAgBAIKMnpJVxHzxo63YAALRWhJDWJjbW3u0AAGilCCGtTUqKFB8vuVz13+5ySQkJNdsBABDAjIeQZcuWKTExUR06dFBSUpK2bNly2u2zsrI0YMAAhYeHKyEhQXfffbe+++67Fqq2Bbjd0tLvp6aeGkRqr2dl1WwHAEAAMxpC1qxZozlz5mjRokXatm2bhgwZotTUVB1sYL7DqlWrdN9992nRokXatWuXli9frjVr1uj+++9v4codlpYmZWdLcadMP42Pr2ln2XYAQBBwWdb3y3AakJSUpBEjRujpp5+WJFVXVyshIUGzZs3SfffdV2f7mTNnateuXcrNzfW2/fd//7fef/99vf322416zLKyMkVFRam0tFSRkZH2PBGneDxSQYFUVFQzByQlhR4QAIAxdn+HGusJqaqq0tatWzVmzJj/FBMSojFjxmjz5s313ufSSy/V1q1bvUM2X3zxhV599VWNGzeuwceprKxUWVmZzyVguN3SqFHSlCk1/xJAAABBxNg6IYcOHZLH41F0dLRPe3R0tD799NN67zN16lQdOnRIP/jBD2RZlk6cOKE77rjjtMMxS5Ys0eLFi22tHQAANJ/xian+yM/P1yOPPKLf/va32rZtm3JycvTKK6/o4YcfbvA+8+bNU2lpqfeyf//+FqwYAAA0xFhPSI8ePeR2u1VSUuLTXlJSopiYmHrvs3DhQt1000269dZbJUmDBg1SRUWFbr/9ds2fP18hIXUzVVhYmMLCwux/AgAAoFmM9YSEhoZq2LBhPpNMq6urlZubq+Tk5Hrvc/To0TpBw/39PAmD82sBAEATGD13zJw5c5SRkaHhw4dr5MiRysrKUkVFhaZPny5JmjZtmuLi4rRkyRJJ0vjx4/XEE0/ooosuUlJSkvbs2aOFCxdq/Pjx3jACAAACg9EQMnnyZH3zzTd64IEHVFxcrKFDh2rDhg3eyar79u3z6flYsGCBXC6XFixYoMLCQvXs2VPjx4/XL3/5S1NPAQAANJHRdUJMCKh1QgAAaEWCZp0QAADQthFCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBF+h5DExEQ99NBD2rdvnxP1AACANsLvEDJ79mzl5OSoX79+uuqqq/Tiiy+qsrLSidoAAEAQa1II2b59u7Zs2aKBAwdq1qxZio2N1cyZM7Vt2zYnagQAAEGo2WfRPX78uH77299q7ty5On78uAYNGqS77rpL06dPl8vlsqtO23AWXQAAmsbu79B2Tb3j8ePHtW7dOq1YsUIbN27UJZdcoltuuUUHDhzQ/fffrzfeeEOrVq1qdoEAACA4+R1Ctm3bphUrVmj16tUKCQnRtGnT9OSTT+q8887zbjNp0iSNGDHC1kIBAEBw8TuEjBgxQldddZWeeeYZTZw4Ue3bt6+zTd++fXX99dfbUiAAAAhOfoeQL774Qn369DntNh07dtSKFSuaXBQAAAh+fh8dc/DgQb3//vt12t9//339v//3/2wpCgAABD+/Q8iMGTO0f//+Ou2FhYWaMWOGLUUBAIDg53cI+eSTT3TxxRfXab/ooov0ySef2FIUAAAIfn6HkLCwMJWUlNRpLyoqUrt2TT7iFwAAtDF+h5Crr75a8+bNU2lpqbftyJEjuv/++3XVVVfZWhwAAAhefnddPP744/rhD3+oPn366KKLLpIkbd++XdHR0XrhhRdsLxAAAAQnv0NIXFycPvroI/35z3/Wjh07FB4erunTp2vKlCn1rhkCAABQnyZN4ujYsaNuv/12u2sBAABtSJNnkn7yySfat2+fqqqqfNp/8pOfNLsoAAAQ/Jq0YuqkSZO0c+dOuVwu1Z6Et/aMuR6Px94KAQBAUPL76JjMzEz17dtXBw8eVEREhP7xj39o06ZNGj58uPLz8x0oEQAABCO/e0I2b96sN998Uz169FBISIhCQkL0gx/8QEuWLNFdd92lDz/80Ik6AQBAkPG7J8Tj8ahz586SpB49eujrr7+WJPXp00e7d++2tzoAABC0/O4JufDCC7Vjxw717dtXSUlJevTRRxUaGqrnnntO/fr1c6JGAAAQhPwOIQsWLFBFRYUk6aGHHtKPf/xjpaSkqHv37lqzZo3tBbZ6Ho9UUCAVFUmxsVJKiuR2m64KAIBWz2XVHt7SDIcPH1bXrl29R8i0ZmVlZYqKilJpaakiIyObt7OcHCkzUzpw4D9t8fHS0qVSWlrz9g0AQCtj63eo/JwTcvz4cbVr104ff/yxT3u3bt0CIoDYKidHSk/3DSCSVFhY056TY6YuAAAChF8hpH379jrrrLNYC8TjqekBqa8TqbZt9uya7QAAQL38Pjpm/vz5uv/++3X48GEn6gkMBQV1e0BOZlnS/v012wEAgHr5PTH16aef1p49e9S7d2/16dNHHTt29Ll927ZtthXXahUV2bsdAABtkN8hZOLEiQ6UEWBiY+3dDgCANsiWo2MCiS0zez0eKTGxZhJqfS+fy1VzlMzevRyuCwAIGkaPjsH33O6aw3ClmsBxstrrWVkEEAAATsPvEBISEiK3293gpc1IS5Oys6W4ON/2+PiadtYJAQDgtPyeE7Ju3Tqf68ePH9eHH36oP/zhD1q8eLFthQWEtDRpwgRWTAUAoAlsmxOyatUqrVmzRn/961/t2J1j7B7PAgCgrWi1c0IuueQS5ebm2rU7AAAQ5GwJIceOHdNvfvMbxZ06PwIAAKABfs8JOfVEdZZl6dtvv1VERIT+9Kc/2VocAAAIXn6HkCeffNInhISEhKhnz55KSkpS165dbS0OAAAEL79DyM033+xAGQAAoK3xe07IihUrtHbt2jrta9eu1R/+8AdbigIAAMHP7xCyZMkS9ejRo057r1699Mgjj9hSFAAACH5+h5B9+/apb9++ddr79Omjffv22VIUAAAIfn6HkF69eumjjz6q075jxw51797dlqIAAEDw8zuETJkyRXfddZfy8vLk8Xjk8Xj05ptvKjMzU9dff70TNQIAgCDk99ExDz/8sL788ktdeeWVateu5u7V1dWaNm0ac0IAAECjNfncMZ999pm2b9+u8PBwDRo0SH369LG7Nkdw7hgAAJrG7u9Qv3tCavXv31/9+/dvdgEAAKBt8ntOyLXXXqtf/epXddofffRR/fSnP7WlKAAAEPz8DiGbNm3SuHHj6rRfc8012rRpky1FAQCA4Od3CCkvL1doaGid9vbt26usrMyWogAAQPDzO4QMGjRIa9asqdP+4osv6vzzz7elKAAAEPz8npi6cOFCpaWl6fPPP9cVV1whScrNzdWqVauUnZ1te4EAACA4+R1Cxo8fr/Xr1+uRRx5Rdna2wsPDNWTIEL355pvq1q2bEzUCAIAg1OR1QmqVlZVp9erVWr58ubZu3SqPx2NXbY5gnRAAAJrG7u9Qv+eE1Nq0aZMyMjLUu3dv/frXv9YVV1yh9957r9kFAQCAtsGv4Zji4mKtXLlSy5cvV1lZma677jpVVlZq/fr1TEoFAAB+aXRPyPjx4zVgwAB99NFHysrK0tdff62nnnrKydoAAEAQa3RPyGuvvaa77rpLd955J8u1AwCAZmt0T8jbb7+tb7/9VsOGDVNSUpKefvppHTp0yMnaAABAEGt0CLnkkkv0+9//XkVFRfrZz36mF198Ub1791Z1dbU2btyob7/91sk6AQBAkGnWIbq7d+/W8uXL9cILL+jIkSO66qqr9PLLL9tZn+04RBcAgKZpNYfoStKAAQP06KOP6sCBA1q9enWziwEAAG1HsxcrCzT0hAAA0DStqicEAACgqQghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIxoFSFk2bJlSkxMVIcOHZSUlKQtW7Y0uO2oUaPkcrnqXH70ox+1YMUAAKC5jIeQNWvWaM6cOVq0aJG2bdumIUOGKDU1VQcPHqx3+5ycHBUVFXkvH3/8sdxut37605+2cOUAAKA5jIeQJ554QrfddpumT5+u888/X88++6wiIiL0/PPP17t9t27dFBMT471s3LhRERERhBAAAAKM0RBSVVWlrVu3asyYMd62kJAQjRkzRps3b27UPpYvX67rr79eHTt2rPf2yspKlZWV+VwAAIB5RkPIoUOH5PF4FB0d7dMeHR2t4uLiM95/y5Yt+vjjj3Xrrbc2uM2SJUsUFRXlvSQkJDS7bgAA0HzGh2OaY/ny5Ro0aJBGjhzZ4Dbz5s1TaWmp97J///4WrBAAADSknckH79Gjh9xut0pKSnzaS0pKFBMTc9r7VlRU6MUXX9RDDz102u3CwsIUFhbW7FoBAIC9jPaEhIaGatiwYcrNzfW2VVdXKzc3V8nJyae979q1a1VZWakbb7zR6TIBAIADjPaESNKcOXOUkZGh4cOHa+TIkcrKylJFRYWmT58uSZo2bZri4uK0ZMkSn/stX75cEydOVPfu3U2UDQAAmsl4CJk8ebK++eYbPfDAAyouLtbQoUO1YcMG72TVffv2KSTEt8Nm9+7devvtt/X3v//dRMkAAMAGLsuyLNNFtKSysjJFRUWptLRUkZGRpssBACBg2P0dGtBHxwAAgMBFCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEa0M11AoPN4PCooKFBRUZFiY2OVkpIit9ttuiwAAFo9Qkgz5OTkKDMzUwcOHPC2xcfHa+nSpUpLSzNYGQAArR/DMU2Uk5Oj9PR0nwAiSYWFhUpPT1dOTo6hygAACAyEkCbweDzKzMyUZVl1bqttmz17tjweT0uXBgBAwCCENEFBQUGdHpCTWZal/fv3q6CgoAWrAgAgsBBCmqCoqMjW7QAAaIsIIU0QGxtr63YAALRFhJAmSElJUXx8vFwuV723u1wuJSQkKCUlpYUrAwAgcBBCmsDtdmvp0qWSVCeI1F7PyspivRAAAE6DENJEaWlpys7OVlxcnE97fHy8srOzWScEAIAzcFn1HWcaxMrKyhQVFaXS0lJFRkY2e3+smAoAaCvs/g5lxdRmcrvdGjVqlOkyAAAIOAzHAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwwHkKWLVumxMREdejQQUlJSdqyZctptz9y5IhmzJih2NhYhYWF6dxzz9Wrr77aQtUCAAC7tDP54GvWrNGcOXP07LPPKikpSVlZWUpNTdXu3bvVq1evOttXVVXpqquuUq9evZSdna24uDh99dVX6tKlS8sXDwAAmsVlWZZl6sGTkpI0YsQIPf3005Kk6upqJSQkaNasWbrvvvvqbP/ss8/qscce06effqr27ds36jEqKytVWVnpvV5WVqaEhASVlpYqMjLSnicCAEAbUFZWpqioKNu+Q40Nx1RVVWnr1q0aM2bMf4oJCdGYMWO0efPmeu/z8ssvKzk5WTNmzFB0dLQuvPBCPfLII/J4PA0+zpIlSxQVFeW9JCQk2P5cAACA/4yFkEOHDsnj8Sg6OtqnPTo6WsXFxfXe54svvlB2drY8Ho9effVVLVy4UL/+9a/1i1/8osHHmTdvnkpLS72X/fv32/o8AABA0xidE+Kv6upq9erVS88995zcbreGDRumwsJCPfbYY1q0aFG99wkLC1NYWFgLVwoAAM7EWAjp0aOH3G63SkpKfNpLSkoUExNT731iY2PVvn17ud1ub9vAgQNVXFysqqoqhYaGOlozAACwj7HhmNDQUA0bNky5ubneturqauXm5io5Obne+1x22WXas2ePqqurvW3//Oc/FRsbSwABACDAGF0nZM6cOfr973+vP/zhD9q1a5fuvPNOVVRUaPr06ZKkadOmad68ed7t77zzTh0+fFiZmZn65z//qVdeeUWPPPKIZsyYYeopAACAJjI6J2Ty5Mn65ptv9MADD6i4uFhDhw7Vhg0bvJNV9+3bp5CQ/+SkhIQEvf7667r77rs1ePBgxcXFKTMzU3PnzjX1FAAAQBMZXSfEBLuPcQYAoK0ImnVCAABA20YIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABjRKkLIsmXLlJiYqA4dOigpKUlbtmxpcNuVK1fK5XL5XDp06NCC1QIAADsYDyFr1qzRnDlztGjRIm3btk1DhgxRamqqDh482OB9IiMjVVRU5L189dVXLVgxAACwg/EQ8sQTT+i2227T9OnTdf755+vZZ59VRESEnn/++Qbv43K5FBMT471ER0e3YMUAAMAO7Uw+eFVVlbZu3ap58+Z520JCQjRmzBht3ry5wfuVl5erT58+qq6u1sUXX6xHHnlEF1xwQb3bVlZWqrKy0nu9tLRUklRWVmbTswAAoG2o/e60LMuW/RkNIYcOHZLH46nTkxEdHa1PP/203vsMGDBAzz//vAYPHqzS0lI9/vjjuvTSS/WPf/xD8fHxdbZfsmSJFi9eXKc9ISHBnicBAEAb869//UtRUVHN3o/RENIUycnJSk5O9l6/9NJLNXDgQP3ud7/Tww8/XGf7efPmac6cOd7r1dXVOnz4sLp37y6Xy2VLTWVlZUpISND+/fsVGRlpyz7RMnjvAhfvXeDivQtcpaWlOuuss9StWzdb9mc0hPTo0UNut1slJSU+7SUlJYqJiWnUPtq3b6+LLrpIe/bsqff2sLAwhYWF+bR16dKlSfWeSWRkJB+oAMV7F7h47wIX713gCgmxZ0qp0YmpoaGhGjZsmHJzc71t1dXVys3N9entOB2Px6OdO3cqNjbWqTIBAIADjA/HzJkzRxkZGRo+fLhGjhyprKwsVVRUaPr06ZKkadOmKS4uTkuWLJEkPfTQQ7rkkkt0zjnn6MiRI3rsscf01Vdf6dZbbzX5NAAAgJ+Mh5DJkyfrm2++0QMPPKDi4mINHTpUGzZs8E5W3bdvn0+3z7///W/ddtttKi4uVteuXTVs2DC9++67Ov/88009BYWFhWnRokV1hn3Q+vHeBS7eu8DFexe47H7vXJZdx9kAAAD4wfhiZQAAoG0ihAAAACMIIQAAwAhCCAAAMIIQYoNly5YpMTFRHTp0UFJSkrZs2WK6JJzBgw8+KJfL5XM577zzTJeFemzatEnjx49X79695XK5tH79ep/bLcvSAw88oNjYWIWHh2vMmDH67LPPzBQLH2d6726++eY6n8OxY8eaKRY+lixZohEjRqhz587q1auXJk6cqN27d/ts891332nGjBnq3r27OnXqpGuvvbbO4qNnQghppjVr1mjOnDlatGiRtm3bpiFDhig1NVUHDx40XRrO4IILLlBRUZH38vbbb5suCfWoqKjQkCFDtGzZsnpvf/TRR/Wb3/xGzz77rN5//3117NhRqamp+u6771q4UpzqTO+dJI0dO9bnc7h69eoWrBANeeuttzRjxgy999572rhxo44fP66rr75aFRUV3m3uvvtu/d///Z/Wrl2rt956S19//bXS0tL8eyALzTJy5EhrxowZ3usej8fq3bu3tWTJEoNV4UwWLVpkDRkyxHQZ8JMka926dd7r1dXVVkxMjPXYY495244cOWKFhYVZq1evNlAhGnLqe2dZlpWRkWFNmDDBSD3wz8GDBy1J1ltvvWVZVs3nrH379tbatWu92+zatcuSZG3evLnR+6UnpBmqqqq0detWjRkzxtsWEhKiMWPGaPPmzQYrQ2N89tln6t27t/r166cbbrhB+/btM10S/LR3714VFxf7fAajoqKUlJTEZzBA5Ofnq1evXhowYIDuvPNO/etf/zJdEupRWloqSd4T123dulXHjx/3+eydd955Ouuss/z67BFCmuHQoUPyeDze1V1rRUdHq7i42FBVaIykpCStXLlSGzZs0DPPPKO9e/cqJSVF3377renS4IfazxmfwcA0duxY/fGPf1Rubq5+9atf6a233tI111wjj8djujScpLq6WrNnz9Zll12mCy+8UFLNZy80NLTOCWH9/ewZX7YdMOGaa67x/vfgwYOVlJSkPn366C9/+YtuueUWg5UBbcf111/v/e9BgwZp8ODBOvvss5Wfn68rr7zSYGU42YwZM/Txxx87Mm+OnpBm6NGjh9xud53ZwCUlJYqJiTFUFZqiS5cuOvfcc7Vnzx7TpcAPtZ8zPoPBoV+/furRowefw1Zk5syZ+tvf/qa8vDzFx8d722NiYlRVVaUjR474bO/vZ48Q0gyhoaEaNmyYcnNzvW3V1dXKzc1VcnKywcrgr/Lycn3++eeKjY01XQr80LdvX8XExPh8BsvKyvT+++/zGQxABw4c0L/+9S8+h62AZVmaOXOm1q1bpzfffFN9+/b1uX3YsGFq3769z2dv9+7d2rdvn1+fPYZjmmnOnDnKyMjQ8OHDNXLkSGVlZamiokLTp083XRpO45577tH48ePVp08fff3111q0aJHcbremTJliujScory83OeX8d69e7V9+3Z169ZNZ511lmbPnq1f/OIX6t+/v/r27auFCxeqd+/emjhxormiIen07123bt20ePFiXXvttYqJidHnn3+ue++9V+ecc45SU1MNVg2pZghm1apV+utf/6rOnTt753lERUUpPDxcUVFRuuWWWzRnzhx169ZNkZGRmjVrlpKTk3XJJZc0/oHsPoynLXrqqaess846ywoNDbVGjhxpvffee6ZLwhlMnjzZio2NtUJDQ624uDhr8uTJ1p49e0yXhXrk5eVZkupcMjIyLMuqOUx34cKFVnR0tBUWFmZdeeWV1u7du80WDcuyTv/eHT161Lr66qutnj17Wu3bt7f69Olj3XbbbVZxcbHpsmFZ9b5vkqwVK1Z4tzl27Jj185//3OratasVERFhTZo0ySoqKvLrcVzfPxgAAECLYk4IAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCICg4HK5tH79etNlAPADIQRAs918881yuVx1LmPHjjVdGoBWjBPYAbDF2LFjtWLFCp+2sLAwQ9UACAT0hACwRVhYmGJiYnwuXbt2lVQzVPLMM8/ommuuUXh4uPr166fs7Gyf++/cuVNXXHGFwsPD1b17d91+++0qLy/32eb555/XBRdcoLCwMMXGxmrmzJk+tx86dEiTJk1SRESE+vfvr5dfftnZJw2gWQghAFrEwoULde2112rHjh264YYbdP3112vXrl2SpIqKCqWmpqpr16764IMPtHbtWr3xxhs+IeOZZ57RjBkzdPvtt2vnzp16+eWXdc455/g8xuLFi3Xdddfpo48+0rhx43TDDTfo8OHDLfo8AfjB1nP/AmiTMjIyLLfbbXXs2NHn8stf/tKyrJrTgt9xxx0+90lKSrLuvPNOy7Is67nnnrO6du1qlZeXe29/5ZVXrJCQEO+p3Xv37m3Nnz+/wRokWQsWLPBeLy8vtyRZr732mm3PE4C9mBMCwBajR4/WM88849PWrVs3738nJyf73JacnKzt27dLknbt2qUhQ4aoY8eO3tsvu+wyVVdXa/fu3XK5XPr666915ZVXnraGwYMHe/+7Y8eOioyM1MGDB5v6lAA4jBACwBYdO3asMzxil/Dw8EZt1759e5/rLpdL1dXVTpQEwAbMCQHQIt5777061wcOHChJGjhwoHbs2KGKigrv7e+8845CQkI0YMAAde7cWYmJicrNzW3RmgE4i54QALaorKxUcXGxT1u7du3Uo0cPSdLatWs1fPhw/eAHP9Cf//xnbdmyRcuXL5ck3XDDDVq0aJEyMjL04IMP6ptvvtGsWbN00003KTo6WpL04IMP6o477lCvXr10zTXX6Ntvv9U777yjWbNmtewTBWAbQggAW2zYsEGxsbE+bQMGDNCnn34qqebIlRdffFE///nPFRsbq9WrV+v888+XJEVEROj1119XZmamRowYoYiICF177bV64oknvPvKyMjQd999pyeffFL33HOPevToofT09JZ7ggBs57IsyzJdBIDg5nK5tG7dOk2cONF0KQBaEeaEAAAAIwghAADACOaEAHAco74A6kNPCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMCI/w+qg7/ja0Jp/AAAAABJRU5ErkJggg==", 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", 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" ] @@ -7327,6 +7847,12 @@ "execution_count": 93, "id": "c6f2d6c4", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:55.889361Z", + "iopub.status.busy": "2023-08-22T06:57:55.889040Z", + "iopub.status.idle": "2023-08-22T06:57:55.894226Z", + "shell.execute_reply": "2023-08-22T06:57:55.893514Z" + }, "lines_to_next_cell": 2 }, "outputs": [], @@ -7354,7 +7880,14 @@ "cell_type": "code", "execution_count": 94, "id": "f3e17682", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:55.899236Z", + "iopub.status.busy": "2023-08-22T06:57:55.898584Z", + "iopub.status.idle": "2023-08-22T06:57:55.919645Z", + "shell.execute_reply": "2023-08-22T06:57:55.918698Z" + } + }, "outputs": [], "source": [ "NYSE = load_data('NYSE')\n", @@ -7379,7 +7912,14 @@ "cell_type": "code", "execution_count": 95, "id": "78707eda", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:55.924653Z", + "iopub.status.busy": "2023-08-22T06:57:55.924212Z", + "iopub.status.idle": "2023-08-22T06:57:55.941488Z", + "shell.execute_reply": "2023-08-22T06:57:55.940914Z" + } + }, "outputs": [], "source": [ "for lag in range(1, 6):\n", @@ -7405,6 +7945,12 @@ "execution_count": 96, "id": "4d894824", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:55.946619Z", + "iopub.status.busy": "2023-08-22T06:57:55.946232Z", + "iopub.status.idle": "2023-08-22T06:57:55.957091Z", + "shell.execute_reply": "2023-08-22T06:57:55.956345Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -7442,7 +7988,14 @@ "cell_type": "code", "execution_count": 97, "id": "4d7f5ce0", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:55.961811Z", + "iopub.status.busy": "2023-08-22T06:57:55.961399Z", + "iopub.status.idle": "2023-08-22T06:57:56.102250Z", + "shell.execute_reply": "2023-08-22T06:57:56.100744Z" + } + }, "outputs": [ { "data": { @@ -7476,6 +8029,12 @@ "execution_count": 98, "id": "a6b371bb", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.107157Z", + "iopub.status.busy": "2023-08-22T06:57:56.106829Z", + "iopub.status.idle": "2023-08-22T06:57:56.120860Z", + "shell.execute_reply": "2023-08-22T06:57:56.120304Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -7500,6 +8059,12 @@ "execution_count": 99, "id": "a2a8cc85", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.124686Z", + "iopub.status.busy": "2023-08-22T06:57:56.124536Z", + "iopub.status.idle": "2023-08-22T06:57:56.148874Z", + "shell.execute_reply": "2023-08-22T06:57:56.148350Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -7552,6 +8117,12 @@ "execution_count": 100, "id": "8ee6e6a3", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.154237Z", + "iopub.status.busy": "2023-08-22T06:57:56.153271Z", + "iopub.status.idle": "2023-08-22T06:57:56.164612Z", + "shell.execute_reply": "2023-08-22T06:57:56.162355Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -7592,6 +8163,12 @@ "execution_count": 101, "id": "d35ceb54", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.168885Z", + "iopub.status.busy": "2023-08-22T06:57:56.168313Z", + "iopub.status.idle": "2023-08-22T06:57:56.177028Z", + "shell.execute_reply": "2023-08-22T06:57:56.174770Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -7629,7 +8206,14 @@ "cell_type": "code", "execution_count": 102, "id": "9e3dc6d5", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.180875Z", + "iopub.status.busy": "2023-08-22T06:57:56.180571Z", + "iopub.status.idle": "2023-08-22T06:57:56.188877Z", + "shell.execute_reply": "2023-08-22T06:57:56.188074Z" + } + }, "outputs": [], "source": [ "class NYSEModel(nn.Module):\n", @@ -7666,7 +8250,14 @@ "cell_type": "code", "execution_count": 103, "id": "df5e5ab6", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.192921Z", + "iopub.status.busy": "2023-08-22T06:57:56.192198Z", + "iopub.status.idle": "2023-08-22T06:57:56.205860Z", + "shell.execute_reply": "2023-08-22T06:57:56.203593Z" + } + }, "outputs": [], "source": [ "datasets = []\n", @@ -7690,6 +8281,12 @@ "execution_count": 104, "id": "d7f49bec", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.209732Z", + "iopub.status.busy": "2023-08-22T06:57:56.209439Z", + "iopub.status.idle": "2023-08-22T06:57:56.224094Z", + "shell.execute_reply": "2023-08-22T06:57:56.221572Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -7707,7 +8304,7 @@ "Total params: 217\n", "Trainable params: 217\n", "Non-trainable params: 0\n", - "Total mult-adds (Units.MEGABYTES): 1.83\n", + "Total mult-adds (M): 1.83\n", "===================================================================================================================\n", "Input size (MB): 0.11\n", "Forward/backward pass size (MB): 0.86\n", @@ -7743,6 +8340,12 @@ "execution_count": 105, "id": "ea7ce0f4", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.228022Z", + "iopub.status.busy": "2023-08-22T06:57:56.227434Z", + "iopub.status.idle": "2023-08-22T06:57:56.236333Z", + "shell.execute_reply": "2023-08-22T06:57:56.234101Z" + }, "lines_to_next_cell": 0 }, "outputs": [], @@ -7766,7 +8369,14 @@ "cell_type": "code", "execution_count": 106, "id": "ccd77738", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:56.242815Z", + "iopub.status.busy": "2023-08-22T06:57:56.242259Z", + "iopub.status.idle": "2023-08-22T06:57:57.426177Z", + "shell.execute_reply": "2023-08-22T06:57:57.425792Z" + } + }, "outputs": [ { "name": "stdout", @@ -7800,7 +8410,14 @@ "cell_type": "code", "execution_count": 107, "id": "96e04e3f", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:57.428165Z", + "iopub.status.busy": "2023-08-22T06:57:57.428026Z", + "iopub.status.idle": "2023-08-22T06:57:57.431868Z", + "shell.execute_reply": "2023-08-22T06:57:57.431594Z" + } + }, "outputs": [], "source": [ "nyse_optimizer = RMSprop(nyse_model.parameters(),\n", @@ -7824,6 +8441,12 @@ "execution_count": 108, "id": "fc6ba2ca", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T06:57:57.433417Z", + "iopub.status.busy": "2023-08-22T06:57:57.433307Z", + "iopub.status.idle": "2023-08-22T07:00:40.275665Z", + "shell.execute_reply": "2023-08-22T07:00:40.275338Z" + }, "lines_to_next_cell": 2 }, "outputs": [ @@ -7850,7 +8473,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "95b6a3cd420043e6b2a2ee4b5c581226", "version_major": 2, "version_minor": 0 }, @@ -7864,7 +8487,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cd881313814b4b319883de36a456b21e", + "model_id": "bbdc8300574e444f84013f84c05e6988", "version_major": 2, "version_minor": 0 }, @@ -7878,7 +8501,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"model_id": "96302a61558d40549b7802f4c44263eb", + "model_id": "38755c7422b34a949cc732c06b1e682e", "version_major": 2, "version_minor": 0 }, @@ -9194,7 +9817,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb7dd989673a4223b66345ef77406828", + "model_id": "0ac4cea1d60b4f79bc3b45b07c38ade8", "version_major": 2, "version_minor": 0 }, @@ -9208,7 +9831,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6e74c6d1b7c64e4596a655a0fbaf1bfb", + "model_id": "758f258102814532b42dda1f53b094a5", "version_major": 2, "version_minor": 0 }, @@ -9222,7 +9845,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d716d0b7820d475ca7653959b52d5450", + "model_id": "8e85659e3769441bae9ba746d0e525ad", "version_major": 2, "version_minor": 0 }, @@ -9236,7 +9859,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "137da5f57ba84efdb51aff612b72db01", + "model_id": "486ae51d02924739bc6a5ca3b3e6d509", "version_major": 2, "version_minor": 0 }, @@ -9250,7 +9873,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bd227089abe34ebda36b2d18df87a86a", + "model_id": "8354aab430d94e518cd1d3e94911337f", "version_major": 2, "version_minor": 0 }, @@ -9264,7 +9887,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "044b5721d12d4dadbc68f2e1ef6db71a", + "model_id": "511a0ae8aad344a69d9e566c023fa35e", "version_major": 2, "version_minor": 0 }, @@ -9278,7 +9901,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cc86818b06a740479b3157b29a1cb18e", + "model_id": "13c285c6471046cbac5ff81f93657c26", "version_major": 2, "version_minor": 0 }, @@ -9292,7 +9915,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "dd634e6fc883498cadcb00911c514371", + "model_id": "977ae5e76c5d44b5b41e8afa239a643d", "version_major": 2, "version_minor": 0 }, @@ -9306,7 +9929,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3a52574849754ad5b349a2ef52a33722", + "model_id": "bf792c29044d4c38b76f2ad756e03da7", "version_major": 2, "version_minor": 0 }, @@ -9320,7 +9943,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "35f1a57c0f6147ce81b036c866a17275", + "model_id": "ce92f452f9314a93afafc2032d615c2d", "version_major": 2, "version_minor": 0 }, @@ -9334,7 +9957,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3cb251ea1f6a4ae7a87fb959e362d392", + "model_id": "279186f508234c3dbbcc710426a1c29e", "version_major": 2, "version_minor": 0 }, @@ -9348,7 +9971,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4e12dfd333064cf5a1fffa8ab56f67a6", + "model_id": "2a4e6adc03ec43bdbca612265317da94", "version_major": 2, "version_minor": 0 }, @@ -9362,7 +9985,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "73e3283065a94da9b0de1b38f87eb801", + "model_id": "cc23610a2bff44898bccc8b2b32ba273", "version_major": 2, "version_minor": 0 }, @@ -9376,7 +9999,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d2755e57697a4a01b6514fdba5578bec", + "model_id": "04dda1d230f74d89a3ee7a5b5d98e726", "version_major": 2, "version_minor": 0 }, @@ -9390,7 +10013,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f8f3787f489f46959322dac484b7ed93", + "model_id": "a654c1113f08483b812944094977a640", "version_major": 2, "version_minor": 0 }, @@ -9404,7 +10027,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f24824825bf644ae831c0e922e16a6c7", + "model_id": "27e31a821ce443eb9009167b3c80f4d8", "version_major": 2, "version_minor": 0 }, @@ -9418,7 +10041,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9abde42fb6564285aef92cdc78ac08a4", + "model_id": "d6aa53936e6544fa81fc40477ff0eb36", "version_major": 2, "version_minor": 0 }, @@ -9432,7 +10055,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "18ab584d1482478b9b7d34e90db79dd1", + "model_id": "74754a163a0248289e40025c911edda2", "version_major": 2, "version_minor": 0 }, @@ -9446,7 +10069,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7b030704b1b545fcad5ee48c27c6b90c", + "model_id": "8c5a887f0b6849038b79dd085b72acf8", "version_major": 2, "version_minor": 0 }, @@ -9460,7 +10083,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c47f07fcd58847b1b24f383546eb653c", + "model_id": "3b02d7e8b4f643c3b4e80b92be4df5a9", "version_major": 2, "version_minor": 0 }, @@ -9474,7 +10097,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f99c0e8c4b65436dafa5c2a9a5452e06", + "model_id": "246618accc3e4cf781e83c608fe100ee", "version_major": 2, "version_minor": 0 }, @@ -9488,7 +10111,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "24f347e1c972488ab6d64bcb07757238", + "model_id": "155223107da644d2b0f7e8d7345de660", "version_major": 2, "version_minor": 0 }, @@ -9502,7 +10125,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cc6b7ff2a86c41cca3a9b423c0297b69", + "model_id": "7d395c5566d740b5b86b9b59bd34deaf", "version_major": 2, "version_minor": 0 }, @@ -9516,7 +10139,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "eeff56e6de874ca3bbacdf08fbcead78", + "model_id": "300178e2115441d5a86263fac06833fb", "version_major": 2, "version_minor": 0 }, @@ -9530,7 +10153,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"model_id": "bdf0d51cecf64b6b88b2189e61e2697d", + "model_id": "d91a8979aa8e4372881dfa4c1d2d0fb8", "version_major": 2, "version_minor": 0 }, @@ -9964,7 +10587,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3663a9cc5dd6492c838b8856ee3db172", + "model_id": "776e0ceb423947fab047fa0a36f1a649", "version_major": 2, "version_minor": 0 }, @@ -9978,7 +10601,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5b8a90932c5c43449baddb012d3f8d2f", + "model_id": "a5939de5d6e2412bba3a5378ff52098f", "version_major": 2, "version_minor": 0 }, @@ -9992,7 +10615,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "acfe2fcbcbeb40b689a942d4a384e81e", + "model_id": "1cb2ef792e7246e78aca5c23ad00754c", "version_major": 2, "version_minor": 0 }, @@ -10006,7 +10629,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a41e9df7b5be41f680c2486bb036eac0", + "model_id": "8577b08dfb83408daa431ebe138d0803", "version_major": 2, "version_minor": 0 }, @@ -10020,7 +10643,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "70cfd7e68ad546fca7b8b4fcb5fe112a", + "model_id": "081e3021531141e48f1cde90a2e60671", "version_major": 2, "version_minor": 0 }, @@ -10034,7 +10657,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "cc6d28f7b6674cc78526f2a04a232f87", + "model_id": "04da4e8a94b8485f9d4f5c355005935f", "version_major": 2, "version_minor": 0 }, @@ -10048,7 +10671,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ae26f55dfe5d44cd9fae433fb8a3ed46", + "model_id": "f4615440ddf24df0a05fc9ff41997f68", "version_major": 2, "version_minor": 0 }, @@ -10062,7 +10685,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b61738f2417244b6b7df1ebb3b3f24d7", + "model_id": "9752977f30eb4c12b2ac52db90ffe806", "version_major": 2, "version_minor": 0 }, @@ -10076,7 +10699,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fdbf1b51bbd54898b58a2de9f695d5ba", + "model_id": "dfa59627c528419aae74ac648e4699c2", "version_major": 2, "version_minor": 0 }, @@ -10090,7 +10713,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d438be1b459e4f0f90e1a26704baa0f1", + "model_id": "626f5be4b8a34439893f6a6bc8045c2c", "version_major": 2, "version_minor": 0 }, @@ -10104,7 +10727,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "164a559d88cd48c58bb43f99cf5819fb", + "model_id": "78123190b7e2489f89d7e56af80f09ca", "version_major": 2, "version_minor": 0 }, @@ -10118,7 +10741,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e142ec45c48e400bbf4cf7dbc8b94e39", + "model_id": "f5d88208fe1f40d79db43eeb3703df18", "version_major": 2, "version_minor": 0 }, @@ -10132,7 +10755,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b98239d615c44f9280cd53bf430b38ef", + "model_id": "74f80b2748054370947e20aef204d640", "version_major": 2, "version_minor": 0 }, @@ -10146,7 +10769,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ee3012ec548c4468ab19394fcc61dfe1", + "model_id": "276324d347834f9fbf90e8acf87776e2", "version_major": 2, "version_minor": 0 }, @@ -10160,7 +10783,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "59abff92475945148512c124b31620ae", + "model_id": "202c78ca5dfc4456adc95c21f0868eee", "version_major": 2, "version_minor": 0 }, @@ -10174,7 +10797,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "10742df4535742c8acdcdbea8d8d6a02", + "model_id": "e9ae73c46ec4448a91b1a66a6212c0c1", "version_major": 2, "version_minor": 0 }, @@ -10188,7 +10811,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7e3d33d2a59f4e2c8413b43cfaee41d1", + "model_id": "fe1f482f4b1b4f47a56a4e97439842b9", "version_major": 2, "version_minor": 0 }, @@ -10202,7 +10825,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1fd03ae4594b4574a55f06d248d8b61a", + "model_id": "7a4b6820418b41faa3d24c135b7fe5ca", "version_major": 2, "version_minor": 0 }, @@ -10216,7 +10839,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "976c6fee189c41b4b5445895fb180c8d", + "model_id": "274c8f91da714f279b9995aa22fc656d", "version_major": 2, "version_minor": 0 }, @@ -10230,7 +10853,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "198e1fa4f5124895bc0ee188984ea726", + "model_id": "1fd9417afaaf423fb91abd1bc89e082c", "version_major": 2, "version_minor": 0 }, @@ -10244,7 +10867,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c78ca1847595417aa71358a1c1b1a4b0", + "model_id": "69162f7af7d446e9892f3865f6f3c204", "version_major": 2, "version_minor": 0 }, @@ -10258,7 +10881,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "af7a5a5a341348f2a0be2f3e77656549", + "model_id": "ce52107f794845beb559296b8df3ca4c", "version_major": 2, "version_minor": 0 }, @@ -10272,7 +10895,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b5ab2cc2a47b42828c7a6780a6db2e00", + "model_id": "039eb58619a04a919785b454d4e75d97", "version_major": 2, "version_minor": 0 }, @@ -10286,7 +10909,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f972c01912c545948b56ea640af2c5b0", + "model_id": "09fd8d108d384f8a81c39661d780d169", "version_major": 2, "version_minor": 0 }, @@ -10300,7 +10923,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "213b3d4ee66d42e1b57a82d35b720112", + "model_id": "25d997f386cf40abb7e1cb6d3ccc492d", "version_major": 2, "version_minor": 0 }, @@ -10314,7 +10937,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ddfc7dcdd1c94636929318d51a61e048", + "model_id": "576f1dfdbc12467ebe290351d695c9bb", "version_major": 2, "version_minor": 0 }, @@ -10328,7 +10951,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3fdce7be7f074ec589421caa0319862f", + "model_id": "f3fb45ebffc4481b98ed10f50a0d45e9", "version_major": 2, "version_minor": 0 }, @@ -10342,7 +10965,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "180334cb0f4c4cc6a5f2eeedc55a986b", + "model_id": "864efaae9ebb4a2cb140e89fb49c4b1a", "version_major": 2, "version_minor": 0 }, @@ -10356,7 +10979,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d2e9e0572d4c48bd9dcf25960be64cde", + "model_id": "ca0d6a01341a41cc84ffacaa43f9ab29", "version_major": 2, "version_minor": 0 }, @@ -10370,7 +10993,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0e26b9ff0a7642e0b8400f0a937eeb30", + "model_id": "cb072b8b7e7f4823acd69e8090be31cf", "version_major": 2, "version_minor": 0 }, @@ -10384,7 +11007,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bf9537d5986b4aacad134c66a4242b0e", + "model_id": "777feac25bc24e619ecbc60c835c124a", "version_major": 2, "version_minor": 0 }, @@ -10398,7 +11021,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e4ab38c6e45d4628b56bbe5dac9458d7", + "model_id": "f89f565d1e07430d97c568d3185a3fcf", "version_major": 2, "version_minor": 0 }, @@ -10412,7 +11035,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "18e800771f6f439bb9f15de7edaf8274", + "model_id": "740d69a62cef481eae149694f26e2d7d", "version_major": 2, "version_minor": 0 }, @@ -10426,7 +11049,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ee30326da017481f94e780628f0ec74d", + "model_id": "781a1d7dd346434cb361755233d1c625", "version_major": 2, "version_minor": 0 }, @@ -10440,7 +11063,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"model_id": "f01094a315c4420e9aba161bd526a1e0", + "model_id": "994179ad8f7f4d65adedba46549b8b8f", "version_major": 2, "version_minor": 0 }, @@ -10524,7 +11147,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "652fb20eb89245a8ac16173eeb553633", + "model_id": "a867c1a31814435b985a017541c07a85", "version_major": 2, "version_minor": 0 }, @@ -10538,7 +11161,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "92757d397a9944e9bf89a627d34d670a", + "model_id": "6e404ac3b2ae4a98b97e1029acf9efc9", "version_major": 2, "version_minor": 0 }, @@ -10552,7 +11175,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d4b73d5c186347d9a05f2486c5baafee", + "model_id": "9b55e6ee243d4823bd15fb8f2f495158", "version_major": 2, "version_minor": 0 }, @@ -10566,7 +11189,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4daeb823d61246a0aa572689807c117d", + "model_id": "e2e7bb6a1da84590b41f8ea9ffb59da6", "version_major": 2, "version_minor": 0 }, @@ -10580,7 +11203,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4da85fb13a6241efa01e2e144209cd5f", + "model_id": "af546f5012484bc5a061a81469ad52b8", "version_major": 2, "version_minor": 0 }, @@ -10594,7 +11217,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6f4c663a0b6449828fcacf1d77b0fad1", + "model_id": "20887ceec3994c03ae2c5c2e3e1a02d6", "version_major": 2, "version_minor": 0 }, @@ -10608,7 +11231,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ada51e9d1ee84f7c8d7cda87a9fed382", + "model_id": "fd444c98f6e74543803b4bbec3706c9d", "version_major": 2, "version_minor": 0 }, @@ -10622,7 +11245,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "035517fa34c84edb8520548a6a6f5f2f", + "model_id": "acab03215fc748008c9ddf873de20a5b", "version_major": 2, "version_minor": 0 }, @@ -10636,7 +11259,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ddc0d23180304537a5d5a408daed4159", + "model_id": "6c01327034f34540830e0810fc97d553", "version_major": 2, "version_minor": 0 }, @@ -10650,7 +11273,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T07:00:40.293426Z", + "iopub.status.busy": "2023-08-22T07:00:40.293319Z", + "iopub.status.idle": "2023-08-22T07:00:40.296658Z", + "shell.execute_reply": "2023-08-22T07:00:40.296393Z" + } + }, "outputs": [], "source": [ "nl_model = NonLinearARModel()\n", @@ -10852,6 +11490,12 @@ "execution_count": 113, "id": "9fc113a1", "metadata": { + "execution": { + "iopub.execute_input": "2023-08-22T07:00:40.298197Z", + "iopub.status.busy": "2023-08-22T07:00:40.298117Z", + "iopub.status.idle": "2023-08-22T07:00:54.837234Z", + "shell.execute_reply": "2023-08-22T07:00:54.836928Z" + }, "lines_to_next_cell": 0 }, "outputs": [ @@ -10878,7 +11522,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "", + "model_id": "60ce6a3ddb494c16a8b3681ec8a1a4b4", "version_major": 2, "version_minor": 0 }, @@ -10892,7 +11536,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6327380ca56a49628cb311d7382fe96d", + "model_id": "3bda25cffd7d41ac8d2636e841039865", "version_major": 2, "version_minor": 0 }, @@ -10906,7 +11550,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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"metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:05.847658Z", - "iopub.status.busy": "2023-08-21T02:30:05.847519Z", - "iopub.status.idle": "2023-08-21T02:30:05.901295Z", - "shell.execute_reply": "2023-08-21T02:30:05.900935Z" + "iopub.execute_input": "2023-08-22T07:00:51.778810Z", + "iopub.status.busy": "2023-08-22T07:00:51.778673Z", + "iopub.status.idle": "2023-08-22T07:00:51.828367Z", + "shell.execute_reply": "2023-08-22T07:00:51.827978Z" }, "lines_to_next_cell": 2 }, @@ -479,10 +479,10 @@ "id": "5f9303dd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:05.903263Z", - "iopub.status.busy": "2023-08-21T02:30:05.903017Z", - "iopub.status.idle": "2023-08-21T02:30:05.930691Z", - "shell.execute_reply": "2023-08-21T02:30:05.930331Z" + "iopub.execute_input": "2023-08-22T07:00:51.830679Z", + "iopub.status.busy": "2023-08-22T07:00:51.830375Z", + "iopub.status.idle": "2023-08-22T07:00:51.855011Z", + "shell.execute_reply": 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"2023-08-22T07:00:51.902771Z", + "shell.execute_reply": "2023-08-22T07:00:51.902284Z" } }, "outputs": [ @@ -826,10 +826,10 @@ "id": "8d999f26", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:05.981441Z", - "iopub.status.busy": "2023-08-21T02:30:05.981315Z", - "iopub.status.idle": "2023-08-21T02:30:05.986317Z", - "shell.execute_reply": "2023-08-21T02:30:05.985949Z" + "iopub.execute_input": "2023-08-22T07:00:51.904821Z", + "iopub.status.busy": "2023-08-22T07:00:51.904683Z", + "iopub.status.idle": "2023-08-22T07:00:51.908678Z", + "shell.execute_reply": "2023-08-22T07:00:51.908230Z" } }, "outputs": [], @@ -859,10 +859,10 @@ "id": "a1f6b355", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:05.988012Z", - "iopub.status.busy": "2023-08-21T02:30:05.987898Z", - "iopub.status.idle": "2023-08-21T02:30:05.993889Z", - "shell.execute_reply": "2023-08-21T02:30:05.993534Z" + "iopub.execute_input": "2023-08-22T07:00:51.910559Z", + "iopub.status.busy": "2023-08-22T07:00:51.910451Z", + "iopub.status.idle": "2023-08-22T07:00:51.916316Z", + "shell.execute_reply": "2023-08-22T07:00:51.915990Z" } }, "outputs": [ @@ -987,10 +987,10 @@ "id": "a1a9d5b3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:05.995682Z", - "iopub.status.busy": "2023-08-21T02:30:05.995549Z", - "iopub.status.idle": "2023-08-21T02:30:06.005479Z", - "shell.execute_reply": "2023-08-21T02:30:06.005089Z" + "iopub.execute_input": "2023-08-22T07:00:51.918281Z", + "iopub.status.busy": "2023-08-22T07:00:51.918144Z", + "iopub.status.idle": "2023-08-22T07:00:51.927845Z", + "shell.execute_reply": "2023-08-22T07:00:51.927490Z" } }, "outputs": [ @@ -1129,10 +1129,10 @@ "id": "1a18b56a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.007172Z", - "iopub.status.busy": "2023-08-21T02:30:06.007049Z", - "iopub.status.idle": "2023-08-21T02:30:06.014185Z", - "shell.execute_reply": "2023-08-21T02:30:06.013870Z" + "iopub.execute_input": "2023-08-22T07:00:51.929658Z", + "iopub.status.busy": "2023-08-22T07:00:51.929522Z", + "iopub.status.idle": "2023-08-22T07:00:51.936112Z", + "shell.execute_reply": "2023-08-22T07:00:51.935793Z" }, "lines_to_next_cell": 0 }, @@ -1290,10 +1290,10 @@ "id": "ff3de29c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.015778Z", - "iopub.status.busy": "2023-08-21T02:30:06.015664Z", - "iopub.status.idle": "2023-08-21T02:30:06.124035Z", - "shell.execute_reply": "2023-08-21T02:30:06.123732Z" + "iopub.execute_input": "2023-08-22T07:00:51.937659Z", + "iopub.status.busy": "2023-08-22T07:00:51.937539Z", + "iopub.status.idle": "2023-08-22T07:00:52.033442Z", + "shell.execute_reply": "2023-08-22T07:00:52.032997Z" }, "lines_to_next_cell": 2 }, @@ -1333,10 +1333,10 @@ "id": "cd9060c1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.125714Z", - "iopub.status.busy": "2023-08-21T02:30:06.125592Z", - "iopub.status.idle": "2023-08-21T02:30:06.243701Z", - "shell.execute_reply": "2023-08-21T02:30:06.243300Z" + "iopub.execute_input": "2023-08-22T07:00:52.035515Z", + "iopub.status.busy": "2023-08-22T07:00:52.035365Z", + "iopub.status.idle": "2023-08-22T07:00:52.186180Z", + "shell.execute_reply": "2023-08-22T07:00:52.185871Z" } }, "outputs": [ @@ -1378,10 +1378,10 @@ "id": "6af7106e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.245493Z", - "iopub.status.busy": "2023-08-21T02:30:06.245357Z", - "iopub.status.idle": "2023-08-21T02:30:06.281521Z", - "shell.execute_reply": "2023-08-21T02:30:06.281138Z" + "iopub.execute_input": "2023-08-22T07:00:52.188568Z", + "iopub.status.busy": "2023-08-22T07:00:52.188400Z", + "iopub.status.idle": "2023-08-22T07:00:52.221771Z", + "shell.execute_reply": "2023-08-22T07:00:52.221413Z" }, "lines_to_next_cell": 2 }, @@ -1467,10 +1467,10 @@ "id": "b6ebefa7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.283282Z", - "iopub.status.busy": "2023-08-21T02:30:06.283123Z", - "iopub.status.idle": "2023-08-21T02:30:06.327003Z", - "shell.execute_reply": "2023-08-21T02:30:06.326646Z" + "iopub.execute_input": "2023-08-22T07:00:52.223735Z", + "iopub.status.busy": "2023-08-22T07:00:52.223584Z", + "iopub.status.idle": "2023-08-22T07:00:52.263558Z", + "shell.execute_reply": "2023-08-22T07:00:52.263236Z" } }, "outputs": [ @@ -1611,10 +1611,10 @@ "id": "098f42ea", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.329058Z", - "iopub.status.busy": "2023-08-21T02:30:06.328927Z", - "iopub.status.idle": "2023-08-21T02:30:06.332782Z", - "shell.execute_reply": "2023-08-21T02:30:06.332425Z" + "iopub.execute_input": "2023-08-22T07:00:52.265430Z", + "iopub.status.busy": "2023-08-22T07:00:52.265309Z", + "iopub.status.idle": "2023-08-22T07:00:52.269361Z", + "shell.execute_reply": "2023-08-22T07:00:52.268968Z" } }, "outputs": [], @@ -1649,10 +1649,10 @@ "id": "26d5d0d0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.334692Z", - "iopub.status.busy": "2023-08-21T02:30:06.334589Z", - "iopub.status.idle": "2023-08-21T02:30:06.344047Z", - "shell.execute_reply": "2023-08-21T02:30:06.343708Z" + "iopub.execute_input": "2023-08-22T07:00:52.271325Z", + "iopub.status.busy": "2023-08-22T07:00:52.271227Z", + "iopub.status.idle": "2023-08-22T07:00:52.280726Z", + "shell.execute_reply": "2023-08-22T07:00:52.280283Z" } }, "outputs": [], @@ -1681,10 +1681,10 @@ "id": "77500663", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.345660Z", - "iopub.status.busy": "2023-08-21T02:30:06.345575Z", - "iopub.status.idle": "2023-08-21T02:30:06.350086Z", - "shell.execute_reply": "2023-08-21T02:30:06.349797Z" + "iopub.execute_input": "2023-08-22T07:00:52.282793Z", + "iopub.status.busy": "2023-08-22T07:00:52.282661Z", + "iopub.status.idle": "2023-08-22T07:00:52.287078Z", + "shell.execute_reply": "2023-08-22T07:00:52.286749Z" } }, "outputs": [ @@ -1793,10 +1793,10 @@ "id": "74324a56", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.351738Z", - "iopub.status.busy": "2023-08-21T02:30:06.351549Z", - "iopub.status.idle": "2023-08-21T02:30:06.444268Z", - "shell.execute_reply": "2023-08-21T02:30:06.441484Z" + "iopub.execute_input": "2023-08-22T07:00:52.289254Z", + "iopub.status.busy": "2023-08-22T07:00:52.289116Z", + "iopub.status.idle": "2023-08-22T07:00:52.327077Z", + "shell.execute_reply": "2023-08-22T07:00:52.313280Z" } }, "outputs": [], @@ -1840,10 +1840,10 @@ "id": "d4be10c2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.449822Z", - "iopub.status.busy": "2023-08-21T02:30:06.449515Z", - "iopub.status.idle": "2023-08-21T02:30:06.458388Z", - "shell.execute_reply": "2023-08-21T02:30:06.457673Z" + "iopub.execute_input": "2023-08-22T07:00:52.360673Z", + "iopub.status.busy": "2023-08-22T07:00:52.360466Z", + "iopub.status.idle": "2023-08-22T07:00:52.386485Z", + "shell.execute_reply": "2023-08-22T07:00:52.383597Z" }, "lines_to_next_cell": 0 }, @@ -1871,10 +1871,10 @@ "id": "c98d396f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.461931Z", - "iopub.status.busy": "2023-08-21T02:30:06.461787Z", - "iopub.status.idle": "2023-08-21T02:30:06.624349Z", - "shell.execute_reply": "2023-08-21T02:30:06.624026Z" + "iopub.execute_input": "2023-08-22T07:00:52.411166Z", + "iopub.status.busy": "2023-08-22T07:00:52.410817Z", + "iopub.status.idle": "2023-08-22T07:00:52.535664Z", + "shell.execute_reply": "2023-08-22T07:00:52.534128Z" } }, "outputs": [], @@ -1900,10 +1900,10 @@ "id": "caf627bc", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.626165Z", - "iopub.status.busy": "2023-08-21T02:30:06.626054Z", - "iopub.status.idle": "2023-08-21T02:30:06.630808Z", - "shell.execute_reply": "2023-08-21T02:30:06.630542Z" + "iopub.execute_input": "2023-08-22T07:00:52.538055Z", + "iopub.status.busy": "2023-08-22T07:00:52.537880Z", + "iopub.status.idle": "2023-08-22T07:00:52.547315Z", + "shell.execute_reply": "2023-08-22T07:00:52.546097Z" }, "lines_to_next_cell": 2 }, @@ -2008,10 +2008,10 @@ "id": "e63242f9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.632357Z", - "iopub.status.busy": "2023-08-21T02:30:06.632261Z", - "iopub.status.idle": "2023-08-21T02:30:06.634630Z", - "shell.execute_reply": "2023-08-21T02:30:06.634305Z" + "iopub.execute_input": "2023-08-22T07:00:52.553567Z", + "iopub.status.busy": "2023-08-22T07:00:52.553399Z", + "iopub.status.idle": "2023-08-22T07:00:52.556617Z", + "shell.execute_reply": "2023-08-22T07:00:52.556076Z" } }, "outputs": [ @@ -2044,10 +2044,10 @@ "id": "338db71d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.636188Z", - "iopub.status.busy": "2023-08-21T02:30:06.636081Z", - "iopub.status.idle": "2023-08-21T02:30:06.791856Z", - "shell.execute_reply": "2023-08-21T02:30:06.791521Z" + "iopub.execute_input": "2023-08-22T07:00:52.558893Z", + "iopub.status.busy": "2023-08-22T07:00:52.558778Z", + "iopub.status.idle": "2023-08-22T07:00:52.706054Z", + "shell.execute_reply": "2023-08-22T07:00:52.705654Z" } }, "outputs": [ @@ -2096,10 +2096,10 @@ "id": "c1db6e15", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.793629Z", - "iopub.status.busy": "2023-08-21T02:30:06.793538Z", - "iopub.status.idle": "2023-08-21T02:30:06.992155Z", - "shell.execute_reply": "2023-08-21T02:30:06.991803Z" + "iopub.execute_input": "2023-08-22T07:00:52.707873Z", + "iopub.status.busy": "2023-08-22T07:00:52.707772Z", + "iopub.status.idle": "2023-08-22T07:00:52.850431Z", + "shell.execute_reply": "2023-08-22T07:00:52.849948Z" } }, "outputs": [ @@ -2152,10 +2152,10 @@ "id": "02ea4212", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:06.993929Z", - "iopub.status.busy": "2023-08-21T02:30:06.993819Z", - "iopub.status.idle": "2023-08-21T02:30:07.011557Z", - "shell.execute_reply": "2023-08-21T02:30:07.011276Z" + "iopub.execute_input": "2023-08-22T07:00:52.852333Z", + "iopub.status.busy": "2023-08-22T07:00:52.852184Z", + "iopub.status.idle": "2023-08-22T07:00:52.869743Z", + "shell.execute_reply": "2023-08-22T07:00:52.869438Z" }, "lines_to_next_cell": 2 }, @@ -2259,10 +2259,10 @@ "id": "0ac610d5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:07.013331Z", - "iopub.status.busy": "2023-08-21T02:30:07.013187Z", - "iopub.status.idle": "2023-08-21T02:30:07.030401Z", - "shell.execute_reply": "2023-08-21T02:30:07.030073Z" + "iopub.execute_input": "2023-08-22T07:00:52.871905Z", + "iopub.status.busy": "2023-08-22T07:00:52.871758Z", + "iopub.status.idle": "2023-08-22T07:00:52.889214Z", + "shell.execute_reply": "2023-08-22T07:00:52.888915Z" }, "lines_to_next_cell": 2 }, @@ -2369,10 +2369,10 @@ "id": "107cedad", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:07.032008Z", - "iopub.status.busy": "2023-08-21T02:30:07.031887Z", - "iopub.status.idle": "2023-08-21T02:30:07.160931Z", - "shell.execute_reply": "2023-08-21T02:30:07.160639Z" + "iopub.execute_input": "2023-08-22T07:00:52.891264Z", + "iopub.status.busy": "2023-08-22T07:00:52.891105Z", + "iopub.status.idle": "2023-08-22T07:00:52.999600Z", + "shell.execute_reply": "2023-08-22T07:00:52.999278Z" }, "lines_to_next_cell": 2 }, @@ -2474,10 +2474,10 @@ "id": "334eb331", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:07.162793Z", - "iopub.status.busy": "2023-08-21T02:30:07.162651Z", - "iopub.status.idle": "2023-08-21T02:30:07.291875Z", - "shell.execute_reply": "2023-08-21T02:30:07.291550Z" + "iopub.execute_input": "2023-08-22T07:00:53.001288Z", + "iopub.status.busy": "2023-08-22T07:00:53.001160Z", + "iopub.status.idle": "2023-08-22T07:00:53.112657Z", + "shell.execute_reply": "2023-08-22T07:00:53.112061Z" }, "lines_to_next_cell": 2 }, @@ -2582,10 +2582,10 @@ "id": "421811c5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:07.293545Z", - "iopub.status.busy": "2023-08-21T02:30:07.293433Z", - "iopub.status.idle": "2023-08-21T02:30:07.532213Z", - "shell.execute_reply": "2023-08-21T02:30:07.531293Z" + "iopub.execute_input": "2023-08-22T07:00:53.115234Z", + "iopub.status.busy": "2023-08-22T07:00:53.114902Z", + "iopub.status.idle": "2023-08-22T07:00:53.349069Z", + "shell.execute_reply": "2023-08-22T07:00:53.326280Z" }, "lines_to_next_cell": 2 }, @@ -2703,7 +2703,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -2716,7 +2716,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch12-unsup-lab.Rmd b/Ch12-unsup-lab.Rmd index 8f885f4..164607a 100644 --- a/Ch12-unsup-lab.Rmd +++ b/Ch12-unsup-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch12-unsup-lab.ipynb b/Ch12-unsup-lab.ipynb index 54b3379..d9a9a1e 100644 --- a/Ch12-unsup-lab.ipynb +++ b/Ch12-unsup-lab.ipynb @@ -22,10 +22,10 @@ "id": "6d5ba583", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:08.846762Z", - "iopub.status.busy": "2023-08-21T02:30:08.846653Z", - "iopub.status.idle": "2023-08-21T02:30:09.939364Z", - "shell.execute_reply": "2023-08-21T02:30:09.939004Z" + "iopub.execute_input": "2023-08-22T07:00:56.821728Z", + "iopub.status.busy": "2023-08-22T07:00:56.821428Z", + "iopub.status.idle": "2023-08-22T07:00:57.569366Z", + "shell.execute_reply": "2023-08-22T07:00:57.569068Z" }, "lines_to_next_cell": 0 }, @@ -55,10 +55,10 @@ "id": "64c83257", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:09.941473Z", - "iopub.status.busy": "2023-08-21T02:30:09.941296Z", - "iopub.status.idle": "2023-08-21T02:30:10.036632Z", - "shell.execute_reply": "2023-08-21T02:30:10.036163Z" + "iopub.execute_input": "2023-08-22T07:00:57.571332Z", + "iopub.status.busy": "2023-08-22T07:00:57.571181Z", + "iopub.status.idle": "2023-08-22T07:00:59.834786Z", + "shell.execute_reply": "2023-08-22T07:00:59.834273Z" } }, "outputs": [], @@ -92,10 +92,10 @@ "id": "04ec4481", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:10.038974Z", - "iopub.status.busy": "2023-08-21T02:30:10.038734Z", - "iopub.status.idle": "2023-08-21T02:30:11.214222Z", - "shell.execute_reply": "2023-08-21T02:30:11.213910Z" + "iopub.execute_input": "2023-08-22T07:00:59.837457Z", + "iopub.status.busy": "2023-08-22T07:00:59.837321Z", + "iopub.status.idle": "2023-08-22T07:01:01.128712Z", + "shell.execute_reply": "2023-08-22T07:01:01.128206Z" } }, "outputs": [ @@ -559,10 +559,10 @@ "id": "1b66036a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.216028Z", - "iopub.status.busy": "2023-08-21T02:30:11.215902Z", - "iopub.status.idle": "2023-08-21T02:30:11.218553Z", - "shell.execute_reply": "2023-08-21T02:30:11.218232Z" + "iopub.execute_input": "2023-08-22T07:01:01.131204Z", + "iopub.status.busy": "2023-08-22T07:01:01.130984Z", + "iopub.status.idle": "2023-08-22T07:01:01.135700Z", + "shell.execute_reply": "2023-08-22T07:01:01.134242Z" } }, "outputs": [ @@ -595,10 +595,10 @@ "id": "52e900fd", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.220090Z", - "iopub.status.busy": "2023-08-21T02:30:11.219971Z", - "iopub.status.idle": "2023-08-21T02:30:11.223332Z", - "shell.execute_reply": "2023-08-21T02:30:11.223004Z" + "iopub.execute_input": "2023-08-22T07:01:01.141963Z", + "iopub.status.busy": "2023-08-22T07:01:01.141493Z", + "iopub.status.idle": "2023-08-22T07:01:01.148106Z", + "shell.execute_reply": "2023-08-22T07:01:01.147604Z" }, "lines_to_next_cell": 2 }, @@ -638,10 +638,10 @@ "id": "68684f78", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.225020Z", - "iopub.status.busy": "2023-08-21T02:30:11.224913Z", - "iopub.status.idle": "2023-08-21T02:30:11.228160Z", - "shell.execute_reply": "2023-08-21T02:30:11.227843Z" + "iopub.execute_input": "2023-08-22T07:01:01.156074Z", + "iopub.status.busy": "2023-08-22T07:01:01.154480Z", + "iopub.status.idle": "2023-08-22T07:01:01.168063Z", + "shell.execute_reply": "2023-08-22T07:01:01.167370Z" } }, "outputs": [ @@ -692,10 +692,10 @@ "id": "d2b7caf9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.229847Z", - "iopub.status.busy": "2023-08-21T02:30:11.229717Z", - "iopub.status.idle": "2023-08-21T02:30:11.233108Z", - "shell.execute_reply": "2023-08-21T02:30:11.232828Z" + "iopub.execute_input": "2023-08-22T07:01:01.171694Z", + "iopub.status.busy": "2023-08-22T07:01:01.171419Z", + "iopub.status.idle": "2023-08-22T07:01:01.175704Z", + "shell.execute_reply": "2023-08-22T07:01:01.174949Z" }, "lines_to_next_cell": 0 }, @@ -722,10 +722,10 @@ "id": "de8f57fa", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.234711Z", - "iopub.status.busy": "2023-08-21T02:30:11.234595Z", - "iopub.status.idle": "2023-08-21T02:30:11.241074Z", - "shell.execute_reply": "2023-08-21T02:30:11.239548Z" + "iopub.execute_input": "2023-08-22T07:01:01.179112Z", + "iopub.status.busy": "2023-08-22T07:01:01.178950Z", + "iopub.status.idle": "2023-08-22T07:01:01.181409Z", + "shell.execute_reply": "2023-08-22T07:01:01.180781Z" }, "lines_to_next_cell": 0 }, @@ -751,10 +751,10 @@ "id": "26c45f1e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.242595Z", - "iopub.status.busy": "2023-08-21T02:30:11.242489Z", - "iopub.status.idle": "2023-08-21T02:30:11.246323Z", - "shell.execute_reply": "2023-08-21T02:30:11.246064Z" + "iopub.execute_input": "2023-08-22T07:01:01.184888Z", + "iopub.status.busy": "2023-08-22T07:01:01.184710Z", + "iopub.status.idle": "2023-08-22T07:01:01.188530Z", + "shell.execute_reply": "2023-08-22T07:01:01.188252Z" } }, "outputs": [ @@ -792,10 +792,10 @@ "id": "3097e99d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.247882Z", - "iopub.status.busy": "2023-08-21T02:30:11.247777Z", - "iopub.status.idle": "2023-08-21T02:30:11.250076Z", - "shell.execute_reply": "2023-08-21T02:30:11.249792Z" + "iopub.execute_input": "2023-08-22T07:01:01.190309Z", + "iopub.status.busy": "2023-08-22T07:01:01.190146Z", + "iopub.status.idle": "2023-08-22T07:01:01.193028Z", + "shell.execute_reply": "2023-08-22T07:01:01.192570Z" } }, "outputs": [ @@ -829,10 +829,10 @@ "id": "c071a242", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.251690Z", - "iopub.status.busy": "2023-08-21T02:30:11.251589Z", - "iopub.status.idle": "2023-08-21T02:30:11.253710Z", - "shell.execute_reply": "2023-08-21T02:30:11.253213Z" + "iopub.execute_input": "2023-08-22T07:01:01.196049Z", + "iopub.status.busy": "2023-08-22T07:01:01.195747Z", + "iopub.status.idle": "2023-08-22T07:01:01.198277Z", + "shell.execute_reply": "2023-08-22T07:01:01.197846Z" }, "lines_to_next_cell": 0 }, @@ -858,10 +858,10 @@ "id": "c9bcab06", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.255475Z", - "iopub.status.busy": "2023-08-21T02:30:11.255331Z", - "iopub.status.idle": "2023-08-21T02:30:11.257666Z", - "shell.execute_reply": "2023-08-21T02:30:11.257404Z" + "iopub.execute_input": "2023-08-22T07:01:01.200305Z", + "iopub.status.busy": "2023-08-22T07:01:01.200177Z", + "iopub.status.idle": "2023-08-22T07:01:01.202888Z", + "shell.execute_reply": "2023-08-22T07:01:01.202483Z" } }, "outputs": [ @@ -901,10 +901,10 @@ "id": "7375ab13", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.259208Z", - "iopub.status.busy": "2023-08-21T02:30:11.259106Z", - "iopub.status.idle": "2023-08-21T02:30:11.411821Z", - "shell.execute_reply": "2023-08-21T02:30:11.411424Z" + "iopub.execute_input": "2023-08-22T07:01:01.204941Z", + "iopub.status.busy": "2023-08-22T07:01:01.204821Z", + "iopub.status.idle": "2023-08-22T07:01:01.305551Z", + "shell.execute_reply": "2023-08-22T07:01:01.304502Z" }, "lines_to_next_cell": 0 }, @@ -951,10 +951,10 @@ "id": "4c1988de", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.413868Z", - "iopub.status.busy": "2023-08-21T02:30:11.413708Z", - "iopub.status.idle": "2023-08-21T02:30:11.510731Z", - "shell.execute_reply": "2023-08-21T02:30:11.510392Z" + "iopub.execute_input": "2023-08-22T07:01:01.308684Z", + "iopub.status.busy": "2023-08-22T07:01:01.308547Z", + "iopub.status.idle": "2023-08-22T07:01:01.398261Z", + "shell.execute_reply": "2023-08-22T07:01:01.397687Z" } }, "outputs": [ @@ -998,10 +998,10 @@ "id": "965c6320", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.512534Z", - "iopub.status.busy": "2023-08-21T02:30:11.512382Z", - "iopub.status.idle": "2023-08-21T02:30:11.515359Z", - "shell.execute_reply": "2023-08-21T02:30:11.514710Z" + "iopub.execute_input": "2023-08-22T07:01:01.400814Z", + "iopub.status.busy": "2023-08-22T07:01:01.400674Z", + "iopub.status.idle": "2023-08-22T07:01:01.404022Z", + "shell.execute_reply": "2023-08-22T07:01:01.403489Z" }, "lines_to_next_cell": 2 }, @@ -1036,10 +1036,10 @@ "id": "cd5e1663", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.517105Z", - "iopub.status.busy": "2023-08-21T02:30:11.516982Z", - "iopub.status.idle": "2023-08-21T02:30:11.519375Z", - "shell.execute_reply": "2023-08-21T02:30:11.519076Z" + "iopub.execute_input": "2023-08-22T07:01:01.405922Z", + "iopub.status.busy": "2023-08-22T07:01:01.405818Z", + "iopub.status.idle": "2023-08-22T07:01:01.409000Z", + "shell.execute_reply": "2023-08-22T07:01:01.408413Z" }, "lines_to_next_cell": 0 }, @@ -1074,10 +1074,10 @@ "id": "e711d1be", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.520951Z", - "iopub.status.busy": "2023-08-21T02:30:11.520847Z", - "iopub.status.idle": "2023-08-21T02:30:11.523283Z", - "shell.execute_reply": "2023-08-21T02:30:11.523005Z" + "iopub.execute_input": "2023-08-22T07:01:01.410782Z", + "iopub.status.busy": "2023-08-22T07:01:01.410676Z", + "iopub.status.idle": "2023-08-22T07:01:01.413542Z", + "shell.execute_reply": "2023-08-22T07:01:01.413036Z" }, "lines_to_next_cell": 0 }, @@ -1115,10 +1115,10 @@ "id": "e122eb41", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.524835Z", - "iopub.status.busy": "2023-08-21T02:30:11.524733Z", - "iopub.status.idle": "2023-08-21T02:30:11.658787Z", - "shell.execute_reply": "2023-08-21T02:30:11.658413Z" + "iopub.execute_input": "2023-08-22T07:01:01.415587Z", + "iopub.status.busy": "2023-08-22T07:01:01.415405Z", + "iopub.status.idle": "2023-08-22T07:01:01.537691Z", + "shell.execute_reply": "2023-08-22T07:01:01.537297Z" }, "lines_to_next_cell": 0 }, @@ -1151,10 +1151,10 @@ "id": "bef47d90", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.661199Z", - "iopub.status.busy": "2023-08-21T02:30:11.661017Z", - "iopub.status.idle": "2023-08-21T02:30:11.782427Z", - "shell.execute_reply": "2023-08-21T02:30:11.781635Z" + "iopub.execute_input": "2023-08-22T07:01:01.540279Z", + "iopub.status.busy": "2023-08-22T07:01:01.539986Z", + "iopub.status.idle": "2023-08-22T07:01:01.632911Z", + "shell.execute_reply": "2023-08-22T07:01:01.632328Z" }, "lines_to_next_cell": 0 }, @@ -1199,10 +1199,10 @@ "id": "f3300d9e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.785513Z", - "iopub.status.busy": "2023-08-21T02:30:11.785329Z", - "iopub.status.idle": "2023-08-21T02:30:11.789028Z", - "shell.execute_reply": "2023-08-21T02:30:11.788419Z" + "iopub.execute_input": "2023-08-22T07:01:01.635302Z", + "iopub.status.busy": "2023-08-22T07:01:01.634975Z", + "iopub.status.idle": "2023-08-22T07:01:01.638324Z", + "shell.execute_reply": "2023-08-22T07:01:01.637831Z" }, "lines_to_next_cell": 0 }, @@ -1248,10 +1248,10 @@ "id": "20e6009f", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.791569Z", - "iopub.status.busy": "2023-08-21T02:30:11.791444Z", - "iopub.status.idle": "2023-08-21T02:30:11.795478Z", - "shell.execute_reply": "2023-08-21T02:30:11.794972Z" + "iopub.execute_input": "2023-08-22T07:01:01.640494Z", + "iopub.status.busy": "2023-08-22T07:01:01.640389Z", + "iopub.status.idle": "2023-08-22T07:01:01.643841Z", + "shell.execute_reply": "2023-08-22T07:01:01.643438Z" }, "lines_to_next_cell": 0 }, @@ -1289,10 +1289,10 @@ "id": "7d9937cf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.797640Z", - "iopub.status.busy": "2023-08-21T02:30:11.797509Z", - "iopub.status.idle": "2023-08-21T02:30:11.800846Z", - "shell.execute_reply": "2023-08-21T02:30:11.800294Z" + "iopub.execute_input": "2023-08-22T07:01:01.646567Z", + "iopub.status.busy": "2023-08-22T07:01:01.646396Z", + "iopub.status.idle": "2023-08-22T07:01:01.649238Z", + "shell.execute_reply": "2023-08-22T07:01:01.648799Z" } }, "outputs": [ @@ -1320,10 +1320,10 @@ "id": "e58f83a3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.808398Z", - "iopub.status.busy": "2023-08-21T02:30:11.808136Z", - "iopub.status.idle": "2023-08-21T02:30:11.811679Z", - "shell.execute_reply": "2023-08-21T02:30:11.811074Z" + "iopub.execute_input": "2023-08-22T07:01:01.651066Z", + "iopub.status.busy": "2023-08-22T07:01:01.650908Z", + "iopub.status.idle": "2023-08-22T07:01:01.653787Z", + "shell.execute_reply": "2023-08-22T07:01:01.653263Z" }, "lines_to_next_cell": 0 }, @@ -1360,10 +1360,10 @@ "id": "5c4f9b34", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.813485Z", - "iopub.status.busy": "2023-08-21T02:30:11.813382Z", - "iopub.status.idle": "2023-08-21T02:30:11.816392Z", - "shell.execute_reply": "2023-08-21T02:30:11.815967Z" + "iopub.execute_input": "2023-08-22T07:01:01.656687Z", + "iopub.status.busy": "2023-08-22T07:01:01.656390Z", + "iopub.status.idle": "2023-08-22T07:01:01.659789Z", + "shell.execute_reply": "2023-08-22T07:01:01.659269Z" } }, "outputs": [ @@ -1390,10 +1390,10 @@ "id": "0ce84f1b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.818183Z", - "iopub.status.busy": "2023-08-21T02:30:11.818037Z", - "iopub.status.idle": "2023-08-21T02:30:11.820586Z", - "shell.execute_reply": "2023-08-21T02:30:11.820295Z" + "iopub.execute_input": "2023-08-22T07:01:01.661783Z", + "iopub.status.busy": "2023-08-22T07:01:01.661671Z", + "iopub.status.idle": "2023-08-22T07:01:01.664431Z", + "shell.execute_reply": "2023-08-22T07:01:01.664078Z" }, "lines_to_next_cell": 0 }, @@ -1435,10 +1435,10 @@ "id": "cd8b4bed", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.822223Z", - "iopub.status.busy": "2023-08-21T02:30:11.822124Z", - "iopub.status.idle": "2023-08-21T02:30:11.824710Z", - "shell.execute_reply": "2023-08-21T02:30:11.824451Z" + "iopub.execute_input": "2023-08-22T07:01:01.666675Z", + "iopub.status.busy": "2023-08-22T07:01:01.666540Z", + "iopub.status.idle": "2023-08-22T07:01:01.669352Z", + "shell.execute_reply": "2023-08-22T07:01:01.668883Z" } }, "outputs": [], @@ -1475,10 +1475,10 @@ "id": "7f3bc8f9", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.826294Z", - "iopub.status.busy": "2023-08-21T02:30:11.826188Z", - "iopub.status.idle": "2023-08-21T02:30:11.828326Z", - "shell.execute_reply": "2023-08-21T02:30:11.827946Z" + "iopub.execute_input": "2023-08-22T07:01:01.671494Z", + "iopub.status.busy": "2023-08-22T07:01:01.671325Z", + "iopub.status.idle": "2023-08-22T07:01:01.673688Z", + "shell.execute_reply": "2023-08-22T07:01:01.673299Z" }, "lines_to_next_cell": 0 }, @@ -1508,10 +1508,10 @@ "id": "771a46a7", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.830112Z", - "iopub.status.busy": "2023-08-21T02:30:11.829990Z", - "iopub.status.idle": "2023-08-21T02:30:11.832019Z", - "shell.execute_reply": "2023-08-21T02:30:11.831653Z" + "iopub.execute_input": "2023-08-22T07:01:01.675631Z", + "iopub.status.busy": "2023-08-22T07:01:01.675424Z", + "iopub.status.idle": "2023-08-22T07:01:01.678059Z", + "shell.execute_reply": "2023-08-22T07:01:01.677393Z" } }, "outputs": [], @@ -1536,10 +1536,10 @@ "id": "1416f048", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.834018Z", - "iopub.status.busy": "2023-08-21T02:30:11.833888Z", - "iopub.status.idle": "2023-08-21T02:30:11.836065Z", - "shell.execute_reply": "2023-08-21T02:30:11.835740Z" + "iopub.execute_input": "2023-08-22T07:01:01.680424Z", + "iopub.status.busy": "2023-08-22T07:01:01.680179Z", + "iopub.status.idle": "2023-08-22T07:01:01.682713Z", + "shell.execute_reply": "2023-08-22T07:01:01.682431Z" }, "lines_to_next_cell": 0 }, @@ -1576,10 +1576,10 @@ "id": "9eff34aa", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.838230Z", - "iopub.status.busy": "2023-08-21T02:30:11.838081Z", - "iopub.status.idle": "2023-08-21T02:30:11.841552Z", - "shell.execute_reply": "2023-08-21T02:30:11.841240Z" + "iopub.execute_input": "2023-08-22T07:01:01.684370Z", + "iopub.status.busy": "2023-08-22T07:01:01.684237Z", + "iopub.status.idle": "2023-08-22T07:01:01.688888Z", + "shell.execute_reply": "2023-08-22T07:01:01.688576Z" } }, "outputs": [ @@ -1631,10 +1631,10 @@ "id": "7815b948", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.843245Z", - "iopub.status.busy": "2023-08-21T02:30:11.843118Z", - "iopub.status.idle": "2023-08-21T02:30:11.846592Z", - "shell.execute_reply": "2023-08-21T02:30:11.846200Z" + "iopub.execute_input": "2023-08-22T07:01:01.690940Z", + "iopub.status.busy": "2023-08-22T07:01:01.690758Z", + "iopub.status.idle": "2023-08-22T07:01:01.694473Z", + "shell.execute_reply": "2023-08-22T07:01:01.694113Z" }, "lines_to_next_cell": 2 }, @@ -1689,10 +1689,10 @@ "id": "f63cf4b8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.848430Z", - "iopub.status.busy": "2023-08-21T02:30:11.848311Z", - "iopub.status.idle": "2023-08-21T02:30:11.850755Z", - "shell.execute_reply": "2023-08-21T02:30:11.850430Z" + "iopub.execute_input": "2023-08-22T07:01:01.697098Z", + "iopub.status.busy": "2023-08-22T07:01:01.696989Z", + "iopub.status.idle": "2023-08-22T07:01:01.699944Z", + "shell.execute_reply": "2023-08-22T07:01:01.699302Z" }, "lines_to_next_cell": 0 }, @@ -1718,10 +1718,10 @@ "id": "f973c2d4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:11.852603Z", - "iopub.status.busy": "2023-08-21T02:30:11.852463Z", - "iopub.status.idle": "2023-08-21T02:30:12.419856Z", - "shell.execute_reply": "2023-08-21T02:30:12.416814Z" + "iopub.execute_input": "2023-08-22T07:01:01.701419Z", + "iopub.status.busy": "2023-08-22T07:01:01.701312Z", + "iopub.status.idle": "2023-08-22T07:01:02.037824Z", + "shell.execute_reply": "2023-08-22T07:01:02.037051Z" }, "lines_to_next_cell": 0 }, @@ -1746,10 +1746,10 @@ "id": "e980954b", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.436151Z", - "iopub.status.busy": "2023-08-21T02:30:12.434738Z", - "iopub.status.idle": "2023-08-21T02:30:12.484691Z", - "shell.execute_reply": "2023-08-21T02:30:12.459324Z" + "iopub.execute_input": "2023-08-22T07:01:02.040614Z", + "iopub.status.busy": "2023-08-22T07:01:02.040437Z", + "iopub.status.idle": "2023-08-22T07:01:02.044054Z", + "shell.execute_reply": "2023-08-22T07:01:02.043563Z" }, "lines_to_next_cell": 0 }, @@ -1788,10 +1788,10 @@ "id": "a94d452c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.510741Z", - "iopub.status.busy": "2023-08-21T02:30:12.510582Z", - "iopub.status.idle": "2023-08-21T02:30:12.636062Z", - "shell.execute_reply": "2023-08-21T02:30:12.635730Z" + "iopub.execute_input": "2023-08-22T07:01:02.046357Z", + "iopub.status.busy": "2023-08-22T07:01:02.046208Z", + "iopub.status.idle": "2023-08-22T07:01:02.149266Z", + "shell.execute_reply": "2023-08-22T07:01:02.148849Z" } }, "outputs": [ @@ -1835,10 +1835,10 @@ "id": "94ff654c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.638065Z", - "iopub.status.busy": "2023-08-21T02:30:12.637921Z", - "iopub.status.idle": "2023-08-21T02:30:12.806481Z", - "shell.execute_reply": "2023-08-21T02:30:12.805717Z" + "iopub.execute_input": "2023-08-22T07:01:02.151742Z", + "iopub.status.busy": "2023-08-22T07:01:02.151594Z", + "iopub.status.idle": "2023-08-22T07:01:02.271388Z", + "shell.execute_reply": "2023-08-22T07:01:02.270932Z" }, "lines_to_next_cell": 0 }, @@ -1884,10 +1884,10 @@ "id": "b3561317", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.808756Z", - "iopub.status.busy": "2023-08-21T02:30:12.808647Z", - "iopub.status.idle": "2023-08-21T02:30:12.868305Z", - "shell.execute_reply": "2023-08-21T02:30:12.867287Z" + "iopub.execute_input": "2023-08-22T07:01:02.274358Z", + "iopub.status.busy": "2023-08-22T07:01:02.273928Z", + "iopub.status.idle": "2023-08-22T07:01:02.290763Z", + "shell.execute_reply": "2023-08-22T07:01:02.290332Z" }, "lines_to_next_cell": 0 }, @@ -1957,10 +1957,10 @@ "id": "be9e4f9c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.871403Z", - "iopub.status.busy": "2023-08-21T02:30:12.871255Z", - "iopub.status.idle": "2023-08-21T02:30:12.877754Z", - "shell.execute_reply": "2023-08-21T02:30:12.877453Z" + "iopub.execute_input": "2023-08-22T07:01:02.293285Z", + "iopub.status.busy": "2023-08-22T07:01:02.293108Z", + "iopub.status.idle": "2023-08-22T07:01:02.297337Z", + "shell.execute_reply": "2023-08-22T07:01:02.296824Z" } }, "outputs": [ @@ -2004,10 +2004,10 @@ "id": "f80d8563", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.879743Z", - "iopub.status.busy": "2023-08-21T02:30:12.879627Z", - "iopub.status.idle": "2023-08-21T02:30:12.883455Z", - "shell.execute_reply": "2023-08-21T02:30:12.883063Z" + "iopub.execute_input": "2023-08-22T07:01:02.299662Z", + "iopub.status.busy": "2023-08-22T07:01:02.299457Z", + "iopub.status.idle": "2023-08-22T07:01:02.303357Z", + "shell.execute_reply": "2023-08-22T07:01:02.302779Z" } }, "outputs": [], @@ -2037,10 +2037,10 @@ "id": "83e7ccf8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.885091Z", - "iopub.status.busy": "2023-08-21T02:30:12.884985Z", - "iopub.status.idle": "2023-08-21T02:30:12.890499Z", - "shell.execute_reply": "2023-08-21T02:30:12.890138Z" + "iopub.execute_input": "2023-08-22T07:01:02.305759Z", + "iopub.status.busy": "2023-08-22T07:01:02.305577Z", + "iopub.status.idle": "2023-08-22T07:01:02.310695Z", + "shell.execute_reply": "2023-08-22T07:01:02.310382Z" } }, "outputs": [ @@ -2097,10 +2097,10 @@ "id": "56ee8cbf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:12.892483Z", - "iopub.status.busy": "2023-08-21T02:30:12.892271Z", - "iopub.status.idle": "2023-08-21T02:30:13.132407Z", - "shell.execute_reply": "2023-08-21T02:30:13.132103Z" + "iopub.execute_input": "2023-08-22T07:01:02.312692Z", + "iopub.status.busy": "2023-08-22T07:01:02.312323Z", + "iopub.status.idle": "2023-08-22T07:01:02.538970Z", + "shell.execute_reply": "2023-08-22T07:01:02.538582Z" } }, "outputs": [ @@ -2142,10 +2142,10 @@ "id": "10f4fc97", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.134084Z", - "iopub.status.busy": "2023-08-21T02:30:13.133962Z", - "iopub.status.idle": "2023-08-21T02:30:13.363909Z", - "shell.execute_reply": "2023-08-21T02:30:13.363594Z" + "iopub.execute_input": "2023-08-22T07:01:02.541376Z", + "iopub.status.busy": "2023-08-22T07:01:02.541208Z", + "iopub.status.idle": "2023-08-22T07:01:02.758968Z", + "shell.execute_reply": "2023-08-22T07:01:02.758508Z" } }, "outputs": [ @@ -2184,10 +2184,10 @@ "id": "3aed342a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.365591Z", - "iopub.status.busy": "2023-08-21T02:30:13.365487Z", - "iopub.status.idle": "2023-08-21T02:30:13.368978Z", - "shell.execute_reply": "2023-08-21T02:30:13.368698Z" + "iopub.execute_input": "2023-08-22T07:01:02.761325Z", + "iopub.status.busy": "2023-08-22T07:01:02.761152Z", + "iopub.status.idle": "2023-08-22T07:01:02.765136Z", + "shell.execute_reply": "2023-08-22T07:01:02.764674Z" } }, "outputs": [ @@ -2226,10 +2226,10 @@ "id": "49c6db0c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.370508Z", - "iopub.status.busy": "2023-08-21T02:30:13.370414Z", - "iopub.status.idle": "2023-08-21T02:30:13.373767Z", - "shell.execute_reply": "2023-08-21T02:30:13.373373Z" + "iopub.execute_input": "2023-08-22T07:01:02.767317Z", + "iopub.status.busy": "2023-08-22T07:01:02.767155Z", + "iopub.status.idle": "2023-08-22T07:01:02.771483Z", + "shell.execute_reply": "2023-08-22T07:01:02.771020Z" } }, "outputs": [ @@ -2312,10 +2312,10 @@ "id": "0ef4b7ec", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.375598Z", - "iopub.status.busy": "2023-08-21T02:30:13.375476Z", - "iopub.status.idle": "2023-08-21T02:30:13.613632Z", - "shell.execute_reply": "2023-08-21T02:30:13.613228Z" + "iopub.execute_input": "2023-08-22T07:01:02.773805Z", + "iopub.status.busy": "2023-08-22T07:01:02.773647Z", + "iopub.status.idle": "2023-08-22T07:01:03.002349Z", + "shell.execute_reply": "2023-08-22T07:01:03.001396Z" } }, "outputs": [ @@ -2367,10 +2367,10 @@ "id": "51761ef3", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.616266Z", - "iopub.status.busy": "2023-08-21T02:30:13.616114Z", - "iopub.status.idle": "2023-08-21T02:30:13.807244Z", - "shell.execute_reply": "2023-08-21T02:30:13.806904Z" + "iopub.execute_input": "2023-08-22T07:01:03.007714Z", + "iopub.status.busy": "2023-08-22T07:01:03.007387Z", + "iopub.status.idle": "2023-08-22T07:01:03.189542Z", + "shell.execute_reply": "2023-08-22T07:01:03.189234Z" }, "lines_to_next_cell": 2 }, @@ -2419,10 +2419,10 @@ "id": "3dbe7baf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.808881Z", - "iopub.status.busy": "2023-08-21T02:30:13.808757Z", - "iopub.status.idle": "2023-08-21T02:30:13.815572Z", - "shell.execute_reply": "2023-08-21T02:30:13.815234Z" + "iopub.execute_input": "2023-08-22T07:01:03.191496Z", + "iopub.status.busy": "2023-08-22T07:01:03.191325Z", + "iopub.status.idle": "2023-08-22T07:01:03.200433Z", + "shell.execute_reply": "2023-08-22T07:01:03.199967Z" } }, "outputs": [], @@ -2452,10 +2452,10 @@ "id": "8f4e9db0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.817455Z", - "iopub.status.busy": "2023-08-21T02:30:13.817327Z", - "iopub.status.idle": "2023-08-21T02:30:13.819934Z", - "shell.execute_reply": "2023-08-21T02:30:13.819588Z" + "iopub.execute_input": "2023-08-22T07:01:03.206306Z", + "iopub.status.busy": "2023-08-22T07:01:03.206039Z", + "iopub.status.idle": "2023-08-22T07:01:03.211349Z", + "shell.execute_reply": "2023-08-22T07:01:03.210526Z" }, "lines_to_next_cell": 2 }, @@ -2489,10 +2489,10 @@ "id": "6373db4d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.821622Z", - "iopub.status.busy": "2023-08-21T02:30:13.821498Z", - "iopub.status.idle": "2023-08-21T02:30:13.825550Z", - "shell.execute_reply": "2023-08-21T02:30:13.825258Z" + "iopub.execute_input": "2023-08-22T07:01:03.215280Z", + "iopub.status.busy": "2023-08-22T07:01:03.215107Z", + "iopub.status.idle": "2023-08-22T07:01:03.220745Z", + "shell.execute_reply": "2023-08-22T07:01:03.220268Z" }, "lines_to_next_cell": 2 }, @@ -2545,10 +2545,10 @@ "id": "9f185f83", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:13.827046Z", - "iopub.status.busy": "2023-08-21T02:30:13.826963Z", - "iopub.status.idle": "2023-08-21T02:30:15.128422Z", - "shell.execute_reply": "2023-08-21T02:30:15.127267Z" + "iopub.execute_input": "2023-08-22T07:01:03.224010Z", + "iopub.status.busy": "2023-08-22T07:01:03.223805Z", + "iopub.status.idle": "2023-08-22T07:01:03.756454Z", + "shell.execute_reply": "2023-08-22T07:01:03.755090Z" } }, "outputs": [], @@ -2577,10 +2577,10 @@ "id": "b044b197", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:15.132319Z", - "iopub.status.busy": "2023-08-21T02:30:15.130836Z", - "iopub.status.idle": "2023-08-21T02:30:15.450531Z", - "shell.execute_reply": "2023-08-21T02:30:15.450148Z" + "iopub.execute_input": "2023-08-22T07:01:03.760531Z", + "iopub.status.busy": "2023-08-22T07:01:03.759964Z", + "iopub.status.idle": "2023-08-22T07:01:04.106389Z", + "shell.execute_reply": "2023-08-22T07:01:04.105861Z" }, "lines_to_next_cell": 0 }, @@ -2647,10 +2647,10 @@ "id": "b2450bb2", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:15.453108Z", - "iopub.status.busy": "2023-08-21T02:30:15.452934Z", - "iopub.status.idle": "2023-08-21T02:30:15.641832Z", - "shell.execute_reply": "2023-08-21T02:30:15.641441Z" + "iopub.execute_input": "2023-08-22T07:01:04.108911Z", + "iopub.status.busy": "2023-08-22T07:01:04.108756Z", + "iopub.status.idle": "2023-08-22T07:01:04.295709Z", + "shell.execute_reply": "2023-08-22T07:01:04.295142Z" }, "lines_to_next_cell": 0 }, @@ -2720,10 +2720,10 @@ "id": "f3f85512", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:15.645761Z", - "iopub.status.busy": "2023-08-21T02:30:15.645577Z", - "iopub.status.idle": "2023-08-21T02:30:15.648982Z", - "shell.execute_reply": "2023-08-21T02:30:15.648549Z" + "iopub.execute_input": "2023-08-22T07:01:04.298506Z", + "iopub.status.busy": "2023-08-22T07:01:04.298369Z", + "iopub.status.idle": "2023-08-22T07:01:04.301034Z", + "shell.execute_reply": "2023-08-22T07:01:04.300583Z" } }, "outputs": [], @@ -2758,10 +2758,10 @@ "id": "5cbeeb19", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:15.651172Z", - "iopub.status.busy": "2023-08-21T02:30:15.651062Z", - "iopub.status.idle": "2023-08-21T02:30:17.138064Z", - "shell.execute_reply": "2023-08-21T02:30:17.137456Z" + "iopub.execute_input": "2023-08-22T07:01:04.303691Z", + "iopub.status.busy": "2023-08-22T07:01:04.303453Z", + "iopub.status.idle": "2023-08-22T07:01:05.507632Z", + "shell.execute_reply": "2023-08-22T07:01:05.507177Z" }, "lines_to_next_cell": 0 }, @@ -2811,10 +2811,10 @@ "id": "1eb3c92e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:17.141105Z", - "iopub.status.busy": "2023-08-21T02:30:17.140950Z", - "iopub.status.idle": "2023-08-21T02:30:17.153308Z", - "shell.execute_reply": "2023-08-21T02:30:17.152985Z" + "iopub.execute_input": "2023-08-22T07:01:05.509745Z", + "iopub.status.busy": "2023-08-22T07:01:05.509610Z", + "iopub.status.idle": "2023-08-22T07:01:05.520162Z", + "shell.execute_reply": "2023-08-22T07:01:05.519790Z" }, "lines_to_next_cell": 2 }, @@ -3005,10 +3005,10 @@ "id": "e3c2841c", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:17.155262Z", - "iopub.status.busy": "2023-08-21T02:30:17.155100Z", - "iopub.status.idle": "2023-08-21T02:30:17.595981Z", - "shell.execute_reply": "2023-08-21T02:30:17.595541Z" + "iopub.execute_input": "2023-08-22T07:01:05.522420Z", + "iopub.status.busy": "2023-08-22T07:01:05.522186Z", + "iopub.status.idle": "2023-08-22T07:01:05.914218Z", + "shell.execute_reply": "2023-08-22T07:01:05.913893Z" } }, "outputs": [ @@ -3054,10 +3054,10 @@ "id": "94dfe5a0", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:17.598183Z", - "iopub.status.busy": "2023-08-21T02:30:17.598049Z", - "iopub.status.idle": "2023-08-21T02:30:46.877046Z", - "shell.execute_reply": "2023-08-21T02:30:46.874804Z" + "iopub.execute_input": "2023-08-22T07:01:05.915828Z", + "iopub.status.busy": "2023-08-22T07:01:05.915706Z", + "iopub.status.idle": "2023-08-22T07:01:06.390699Z", + "shell.execute_reply": "2023-08-22T07:01:06.390367Z" } }, "outputs": [ @@ -3179,10 +3179,10 @@ "id": "abd51940", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:30:46.888673Z", - "iopub.status.busy": "2023-08-21T02:30:46.888240Z", - "iopub.status.idle": "2023-08-21T02:30:47.344737Z", - "shell.execute_reply": "2023-08-21T02:30:47.344286Z" + "iopub.execute_input": "2023-08-22T07:01:06.404283Z", + "iopub.status.busy": "2023-08-22T07:01:06.404155Z", + "iopub.status.idle": "2023-08-22T07:01:06.897582Z", + "shell.execute_reply": "2023-08-22T07:01:06.897221Z" }, "lines_to_next_cell": 0 }, @@ -3392,7 +3392,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -3405,7 +3405,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/Ch13-multiple-lab.Rmd b/Ch13-multiple-lab.Rmd index bee30c3..59d7b73 100644 --- a/Ch13-multiple-lab.Rmd +++ b/Ch13-multiple-lab.Rmd @@ -2,7 +2,7 @@ jupyter: jupytext: cell_metadata_filter: -all - formats: ipynb,Rmd + formats: Rmd,ipynb main_language: python text_representation: extension: .Rmd diff --git a/Ch13-multiple-lab.ipynb b/Ch13-multiple-lab.ipynb index bb9684d..0e8886d 100644 --- a/Ch13-multiple-lab.ipynb +++ b/Ch13-multiple-lab.ipynb @@ -26,10 +26,10 @@ "id": "7cc4fbeb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:16.417394Z", - "iopub.status.busy": "2023-08-21T02:29:16.417287Z", - "iopub.status.idle": "2023-08-21T02:29:17.613483Z", - "shell.execute_reply": "2023-08-21T02:29:17.613156Z" + "iopub.execute_input": "2023-08-22T07:01:10.471948Z", + "iopub.status.busy": "2023-08-22T07:01:10.471668Z", + "iopub.status.idle": "2023-08-22T07:01:11.350943Z", + "shell.execute_reply": "2023-08-22T07:01:11.350643Z" } }, "outputs": [], @@ -56,10 +56,10 @@ "id": "595efc18", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.615551Z", - "iopub.status.busy": "2023-08-21T02:29:17.615375Z", - "iopub.status.idle": "2023-08-21T02:29:17.617379Z", - "shell.execute_reply": "2023-08-21T02:29:17.617087Z" + "iopub.execute_input": "2023-08-22T07:01:11.352807Z", + "iopub.status.busy": "2023-08-22T07:01:11.352663Z", + "iopub.status.idle": "2023-08-22T07:01:11.354553Z", + "shell.execute_reply": "2023-08-22T07:01:11.354339Z" }, "lines_to_next_cell": 2 }, @@ -95,10 +95,10 @@ "id": "985d1d6e", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.618995Z", - "iopub.status.busy": "2023-08-21T02:29:17.618887Z", - "iopub.status.idle": "2023-08-21T02:29:17.620921Z", - "shell.execute_reply": "2023-08-21T02:29:17.620629Z" + "iopub.execute_input": "2023-08-22T07:01:11.355962Z", + "iopub.status.busy": "2023-08-22T07:01:11.355865Z", + "iopub.status.idle": "2023-08-22T07:01:11.357829Z", + "shell.execute_reply": "2023-08-22T07:01:11.357602Z" } }, "outputs": [], @@ -125,10 +125,10 @@ "id": "753d612a", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.622537Z", - "iopub.status.busy": "2023-08-21T02:29:17.622429Z", - "iopub.status.idle": "2023-08-21T02:29:17.626063Z", - "shell.execute_reply": "2023-08-21T02:29:17.625801Z" + "iopub.execute_input": "2023-08-22T07:01:11.359164Z", + "iopub.status.busy": "2023-08-22T07:01:11.359072Z", + "iopub.status.idle": "2023-08-22T07:01:11.362315Z", + "shell.execute_reply": "2023-08-22T07:01:11.362065Z" } }, "outputs": [ @@ -172,10 +172,10 @@ "id": "facd6569", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.627714Z", - "iopub.status.busy": "2023-08-21T02:29:17.627617Z", - "iopub.status.idle": "2023-08-21T02:29:17.651726Z", - "shell.execute_reply": "2023-08-21T02:29:17.651448Z" + "iopub.execute_input": "2023-08-22T07:01:11.363675Z", + "iopub.status.busy": "2023-08-22T07:01:11.363598Z", + "iopub.status.idle": "2023-08-22T07:01:11.382551Z", + "shell.execute_reply": "2023-08-22T07:01:11.382313Z" }, "lines_to_next_cell": 0 }, @@ -208,10 +208,10 @@ "id": "e89ef3eb", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.653344Z", - "iopub.status.busy": "2023-08-21T02:29:17.653256Z", - "iopub.status.idle": "2023-08-21T02:29:17.662644Z", - "shell.execute_reply": "2023-08-21T02:29:17.662346Z" + "iopub.execute_input": "2023-08-22T07:01:11.384012Z", + "iopub.status.busy": "2023-08-22T07:01:11.383929Z", + "iopub.status.idle": "2023-08-22T07:01:11.390854Z", + "shell.execute_reply": "2023-08-22T07:01:11.390622Z" }, "lines_to_next_cell": 0 }, @@ -309,10 +309,10 @@ "id": "ae184aaf", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.664327Z", - "iopub.status.busy": "2023-08-21T02:29:17.664213Z", - "iopub.status.idle": "2023-08-21T02:29:17.690928Z", - "shell.execute_reply": "2023-08-21T02:29:17.690657Z" + "iopub.execute_input": "2023-08-22T07:01:11.392278Z", + "iopub.status.busy": "2023-08-22T07:01:11.392193Z", + "iopub.status.idle": "2023-08-22T07:01:11.414541Z", + "shell.execute_reply": "2023-08-22T07:01:11.414284Z" }, "lines_to_next_cell": 0 }, @@ -421,10 +421,10 @@ "id": "0295fe68", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.692568Z", - "iopub.status.busy": "2023-08-21T02:29:17.692459Z", - "iopub.status.idle": "2023-08-21T02:29:17.899403Z", - "shell.execute_reply": "2023-08-21T02:29:17.899081Z" + "iopub.execute_input": "2023-08-22T07:01:11.416013Z", + "iopub.status.busy": "2023-08-22T07:01:11.415934Z", + "iopub.status.idle": "2023-08-22T07:01:11.601337Z", + "shell.execute_reply": "2023-08-22T07:01:11.601050Z" } }, "outputs": [ @@ -477,10 +477,10 @@ "id": "406e59a8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.901146Z", - "iopub.status.busy": "2023-08-21T02:29:17.901041Z", - "iopub.status.idle": "2023-08-21T02:29:17.939312Z", - "shell.execute_reply": "2023-08-21T02:29:17.939019Z" + "iopub.execute_input": "2023-08-22T07:01:11.603043Z", + "iopub.status.busy": "2023-08-22T07:01:11.602922Z", + "iopub.status.idle": "2023-08-22T07:01:11.637677Z", + "shell.execute_reply": "2023-08-22T07:01:11.637393Z" } }, "outputs": [ @@ -545,10 +545,10 @@ "id": "d4f6a247", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.941032Z", - "iopub.status.busy": "2023-08-21T02:29:17.940919Z", - "iopub.status.idle": "2023-08-21T02:29:17.943369Z", - "shell.execute_reply": "2023-08-21T02:29:17.943081Z" + "iopub.execute_input": "2023-08-22T07:01:11.639421Z", + "iopub.status.busy": "2023-08-22T07:01:11.639308Z", + "iopub.status.idle": "2023-08-22T07:01:11.641724Z", + "shell.execute_reply": "2023-08-22T07:01:11.641464Z" }, "lines_to_next_cell": 2 }, @@ -584,10 +584,10 @@ "id": "01a29d71", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.944859Z", - "iopub.status.busy": "2023-08-21T02:29:17.944760Z", - "iopub.status.idle": "2023-08-21T02:29:17.946888Z", - "shell.execute_reply": "2023-08-21T02:29:17.946639Z" + "iopub.execute_input": "2023-08-22T07:01:11.643173Z", + "iopub.status.busy": "2023-08-22T07:01:11.643074Z", + "iopub.status.idle": "2023-08-22T07:01:11.645284Z", + "shell.execute_reply": "2023-08-22T07:01:11.645035Z" } }, "outputs": [ @@ -626,10 +626,10 @@ "id": "95454eb4", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.948474Z", - "iopub.status.busy": "2023-08-21T02:29:17.948372Z", - "iopub.status.idle": "2023-08-21T02:29:17.990740Z", - "shell.execute_reply": "2023-08-21T02:29:17.990464Z" + "iopub.execute_input": "2023-08-22T07:01:11.646828Z", + "iopub.status.busy": "2023-08-22T07:01:11.646723Z", + "iopub.status.idle": "2023-08-22T07:01:11.681328Z", + "shell.execute_reply": "2023-08-22T07:01:11.681006Z" }, "lines_to_next_cell": 2 }, @@ -666,10 +666,10 @@ "id": "1f1ac764", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.992261Z", - "iopub.status.busy": "2023-08-21T02:29:17.992149Z", - "iopub.status.idle": "2023-08-21T02:29:17.995141Z", - "shell.execute_reply": "2023-08-21T02:29:17.994894Z" + "iopub.execute_input": "2023-08-22T07:01:11.683039Z", + "iopub.status.busy": "2023-08-22T07:01:11.682931Z", + "iopub.status.idle": "2023-08-22T07:01:11.685981Z", + "shell.execute_reply": "2023-08-22T07:01:11.685726Z" }, "lines_to_next_cell": 2 }, @@ -710,10 +710,10 @@ "id": "298d975d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:17.996686Z", - "iopub.status.busy": "2023-08-21T02:29:17.996590Z", - "iopub.status.idle": "2023-08-21T02:29:17.999332Z", - "shell.execute_reply": "2023-08-21T02:29:17.999076Z" + "iopub.execute_input": "2023-08-22T07:01:11.687516Z", + "iopub.status.busy": "2023-08-22T07:01:11.687436Z", + "iopub.status.idle": "2023-08-22T07:01:11.690137Z", + "shell.execute_reply": "2023-08-22T07:01:11.689879Z" } }, "outputs": [ @@ -762,10 +762,10 @@ "id": "be117713", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:18.000853Z", - "iopub.status.busy": "2023-08-21T02:29:18.000747Z", - "iopub.status.idle": "2023-08-21T02:29:18.487357Z", - "shell.execute_reply": "2023-08-21T02:29:18.487078Z" + "iopub.execute_input": "2023-08-22T07:01:11.691729Z", + "iopub.status.busy": "2023-08-22T07:01:11.691643Z", + "iopub.status.idle": "2023-08-22T07:01:12.083351Z", + "shell.execute_reply": "2023-08-22T07:01:12.083006Z" }, "lines_to_next_cell": 2 }, @@ -822,10 +822,10 @@ "id": "537c4ea8", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:18.489069Z", - "iopub.status.busy": "2023-08-21T02:29:18.488949Z", - "iopub.status.idle": "2023-08-21T02:29:18.570869Z", - "shell.execute_reply": "2023-08-21T02:29:18.570427Z" + "iopub.execute_input": "2023-08-22T07:01:12.085028Z", + "iopub.status.busy": "2023-08-22T07:01:12.084925Z", + "iopub.status.idle": "2023-08-22T07:01:12.158318Z", + "shell.execute_reply": "2023-08-22T07:01:12.158031Z" } }, "outputs": [ @@ -863,10 +863,10 @@ "id": "2c88ec87", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:18.572454Z", - "iopub.status.busy": "2023-08-21T02:29:18.572341Z", - "iopub.status.idle": "2023-08-21T02:29:19.005707Z", - "shell.execute_reply": "2023-08-21T02:29:19.005387Z" + "iopub.execute_input": "2023-08-22T07:01:12.160012Z", + "iopub.status.busy": "2023-08-22T07:01:12.159900Z", + "iopub.status.idle": "2023-08-22T07:01:12.510866Z", + "shell.execute_reply": "2023-08-22T07:01:12.510573Z" } }, "outputs": [], @@ -892,10 +892,10 @@ "id": "b6d56819", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.007847Z", - "iopub.status.busy": "2023-08-21T02:29:19.007564Z", - "iopub.status.idle": "2023-08-21T02:29:19.010742Z", - "shell.execute_reply": "2023-08-21T02:29:19.010371Z" + "iopub.execute_input": "2023-08-22T07:01:12.512518Z", + "iopub.status.busy": "2023-08-22T07:01:12.512432Z", + "iopub.status.idle": "2023-08-22T07:01:12.514982Z", + "shell.execute_reply": "2023-08-22T07:01:12.514769Z" } }, "outputs": [ @@ -937,10 +937,10 @@ "id": "b00da3a1", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.012400Z", - "iopub.status.busy": "2023-08-21T02:29:19.012298Z", - "iopub.status.idle": "2023-08-21T02:29:19.015314Z", - "shell.execute_reply": "2023-08-21T02:29:19.014978Z" + "iopub.execute_input": "2023-08-22T07:01:12.516361Z", + "iopub.status.busy": "2023-08-22T07:01:12.516283Z", + "iopub.status.idle": "2023-08-22T07:01:12.518438Z", + "shell.execute_reply": "2023-08-22T07:01:12.518191Z" }, "lines_to_next_cell": 0 }, @@ -981,10 +981,10 @@ "id": "1c230117", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.016857Z", - "iopub.status.busy": "2023-08-21T02:29:19.016769Z", - "iopub.status.idle": "2023-08-21T02:29:19.019332Z", - "shell.execute_reply": "2023-08-21T02:29:19.019032Z" + "iopub.execute_input": "2023-08-22T07:01:12.519863Z", + "iopub.status.busy": "2023-08-22T07:01:12.519780Z", + "iopub.status.idle": "2023-08-22T07:01:12.521828Z", + "shell.execute_reply": "2023-08-22T07:01:12.521610Z" }, "lines_to_next_cell": 2 }, @@ -1031,10 +1031,10 @@ "id": "62289650", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.021112Z", - "iopub.status.busy": "2023-08-21T02:29:19.020904Z", - "iopub.status.idle": "2023-08-21T02:29:19.023622Z", - "shell.execute_reply": "2023-08-21T02:29:19.023338Z" + "iopub.execute_input": "2023-08-22T07:01:12.523116Z", + "iopub.status.busy": "2023-08-22T07:01:12.523043Z", + "iopub.status.idle": "2023-08-22T07:01:12.525236Z", + "shell.execute_reply": "2023-08-22T07:01:12.525021Z" } }, "outputs": [], @@ -1065,10 +1065,10 @@ "id": "18b3c0ed", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.025191Z", - "iopub.status.busy": "2023-08-21T02:29:19.025074Z", - "iopub.status.idle": "2023-08-21T02:29:19.262207Z", - "shell.execute_reply": "2023-08-21T02:29:19.261823Z" + "iopub.execute_input": "2023-08-22T07:01:12.526613Z", + "iopub.status.busy": "2023-08-22T07:01:12.526539Z", + "iopub.status.idle": "2023-08-22T07:01:12.740275Z", + "shell.execute_reply": "2023-08-22T07:01:12.739986Z" }, "lines_to_next_cell": 2 }, @@ -1115,10 +1115,10 @@ "id": "eb79e606", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.264174Z", - "iopub.status.busy": "2023-08-21T02:29:19.264030Z", - "iopub.status.idle": "2023-08-21T02:29:19.339232Z", - "shell.execute_reply": "2023-08-21T02:29:19.338912Z" + "iopub.execute_input": "2023-08-22T07:01:12.742002Z", + "iopub.status.busy": "2023-08-22T07:01:12.741882Z", + "iopub.status.idle": "2023-08-22T07:01:12.844984Z", + "shell.execute_reply": "2023-08-22T07:01:12.844724Z" }, "lines_to_next_cell": 2 }, @@ -1166,10 +1166,10 @@ "id": "1afbcf47", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.341009Z", - "iopub.status.busy": "2023-08-21T02:29:19.340889Z", - "iopub.status.idle": "2023-08-21T02:29:19.344670Z", - "shell.execute_reply": "2023-08-21T02:29:19.344391Z" + "iopub.execute_input": "2023-08-22T07:01:12.846468Z", + "iopub.status.busy": "2023-08-22T07:01:12.846384Z", + "iopub.status.idle": "2023-08-22T07:01:12.849714Z", + "shell.execute_reply": "2023-08-22T07:01:12.849454Z" }, "lines_to_next_cell": 2 }, @@ -1219,10 +1219,10 @@ "id": "f73f4c6d", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:19.346368Z", - "iopub.status.busy": "2023-08-21T02:29:19.346227Z", - "iopub.status.idle": "2023-08-21T02:29:21.776569Z", - "shell.execute_reply": "2023-08-21T02:29:21.776267Z" + "iopub.execute_input": "2023-08-22T07:01:12.851134Z", + "iopub.status.busy": "2023-08-22T07:01:12.851053Z", + "iopub.status.idle": "2023-08-22T07:01:14.848052Z", + "shell.execute_reply": "2023-08-22T07:01:14.847788Z" }, "lines_to_next_cell": 2 }, @@ -1270,10 +1270,10 @@ "id": "062daf19", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:21.778366Z", - "iopub.status.busy": "2023-08-21T02:29:21.778242Z", - "iopub.status.idle": "2023-08-21T02:29:21.990476Z", - "shell.execute_reply": "2023-08-21T02:29:21.989965Z" + "iopub.execute_input": "2023-08-22T07:01:14.849560Z", + "iopub.status.busy": "2023-08-22T07:01:14.849477Z", + "iopub.status.idle": "2023-08-22T07:01:14.990286Z", + "shell.execute_reply": "2023-08-22T07:01:14.989980Z" }, "lines_to_next_cell": 0 }, @@ -1330,10 +1330,10 @@ "id": "6d14fcad", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:29:21.992665Z", - "iopub.status.busy": "2023-08-21T02:29:21.992515Z", - "iopub.status.idle": "2023-08-21T02:34:05.930300Z", - "shell.execute_reply": "2023-08-21T02:34:05.929181Z" + "iopub.execute_input": "2023-08-22T07:01:14.992440Z", + "iopub.status.busy": "2023-08-22T07:01:14.992326Z", + "iopub.status.idle": "2023-08-22T07:04:36.802040Z", + "shell.execute_reply": "2023-08-22T07:04:36.801740Z" } }, "outputs": [], @@ -1376,10 +1376,10 @@ "id": "8f0ec909", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:34:05.935513Z", - "iopub.status.busy": "2023-08-21T02:34:05.935323Z", - "iopub.status.idle": "2023-08-21T02:34:06.118079Z", - "shell.execute_reply": "2023-08-21T02:34:06.117633Z" + "iopub.execute_input": "2023-08-22T07:04:36.803805Z", + "iopub.status.busy": "2023-08-22T07:04:36.803712Z", + "iopub.status.idle": "2023-08-22T07:04:36.913862Z", + "shell.execute_reply": "2023-08-22T07:04:36.913579Z" } }, "outputs": [], @@ -1417,10 +1417,10 @@ "id": "f11339e5", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:34:06.120138Z", - "iopub.status.busy": "2023-08-21T02:34:06.119994Z", - "iopub.status.idle": "2023-08-21T02:34:06.123846Z", - "shell.execute_reply": "2023-08-21T02:34:06.123478Z" + "iopub.execute_input": "2023-08-22T07:04:36.915631Z", + "iopub.status.busy": "2023-08-22T07:04:36.915542Z", + "iopub.status.idle": "2023-08-22T07:04:36.918059Z", + "shell.execute_reply": "2023-08-22T07:04:36.917797Z" } }, "outputs": [ @@ -1472,10 +1472,10 @@ "id": "d2600773", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:34:06.126460Z", - "iopub.status.busy": "2023-08-21T02:34:06.126346Z", - "iopub.status.idle": "2023-08-21T02:34:06.129561Z", - "shell.execute_reply": "2023-08-21T02:34:06.129124Z" + "iopub.execute_input": "2023-08-22T07:04:36.919428Z", + "iopub.status.busy": "2023-08-22T07:04:36.919345Z", + "iopub.status.idle": "2023-08-22T07:04:36.921649Z", + "shell.execute_reply": "2023-08-22T07:04:36.921430Z" } }, "outputs": [ @@ -1540,10 +1540,10 @@ "id": "924b7705", "metadata": { "execution": { - "iopub.execute_input": "2023-08-21T02:34:06.131323Z", - "iopub.status.busy": "2023-08-21T02:34:06.131207Z", - "iopub.status.idle": "2023-08-21T02:34:06.216626Z", - "shell.execute_reply": "2023-08-21T02:34:06.216270Z" + "iopub.execute_input": "2023-08-22T07:04:36.923042Z", + "iopub.status.busy": "2023-08-22T07:04:36.922969Z", + "iopub.status.idle": "2023-08-22T07:04:36.986633Z", + "shell.execute_reply": "2023-08-22T07:04:36.986366Z" }, "lines_to_next_cell": 0 }, @@ -1578,7 +1578,7 @@ "metadata": { "jupytext": { "cell_metadata_filter": "-all", - "formats": "ipynb,Rmd", + "formats": "Rmd,ipynb", "main_language": "python" }, "language_info": { @@ -1591,7 +1591,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4,