diff --git a/Ch10-deeplearning-lab.ipynb b/Ch10-deeplearning-lab.ipynb index 516f3c8..c7e788c 100644 --- a/Ch10-deeplearning-lab.ipynb +++ b/Ch10-deeplearning-lab.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "fd22c2e6", + "id": "b672dcf6", "metadata": {}, "source": [ "\n", @@ -18,13 +18,13 @@ "[pytorch.org/tutorials](https://pytorch.org/tutorials/beginner/basics/intro.html).\n", "Much of our code is adapted from there, as well as the `pytorch_lightning` documentation. {The precise URLs at the time of writing are and .}\n", "\n", - "We start with several standard imports that we have seen in other contexts." + "We start with several standard imports that we have seen before." ] }, { "cell_type": "code", "execution_count": 1, - "id": "aeb913e2", + "id": "9b5b8319", "metadata": { "lines_to_next_cell": 2 }, @@ -48,7 +48,7 @@ }, { "cell_type": "markdown", - "id": "36a4ac8d", + "id": "c0cb2c87", "metadata": {}, "source": [ "### Torch-Specific Imports\n", @@ -61,7 +61,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "3a3e91e7", + "id": "f66f362c", "metadata": {}, "outputs": [], "source": [ @@ -73,7 +73,7 @@ }, { "cell_type": "markdown", - "id": "6e89c676", + "id": "5ce27a8d", "metadata": {}, "source": [ "There are several other helper packages for `torch`. For instance,\n", @@ -87,19 +87,18 @@ { "cell_type": "code", "execution_count": 3, - "id": "3f4fdb8c", + "id": "17bce9cb", "metadata": {}, "outputs": [], "source": [ "from torchmetrics import (MeanAbsoluteError,\n", " R2Score)\n", - "from torchinfo import summary\n", - "from torchvision.io import read_image\n" + "from torchinfo import summary\n" ] }, { "cell_type": "markdown", - "id": "b7b12e5c", + "id": "a14990c3", "metadata": {}, "source": [ "The package `pytorch_lightning` is a somewhat higher-level\n", @@ -112,7 +111,7 @@ { "cell_type": "code", "execution_count": 4, - "id": "71cc6f03", + "id": "4c3b6e43", "metadata": {}, "outputs": [], "source": [ @@ -122,7 +121,7 @@ }, { "cell_type": "markdown", - "id": "8394fc0a", + "id": "e5bc78bd", "metadata": {}, "source": [ "In order to reproduce results we use `seed_everything()`. We will also instruct `torch` to use deterministic algorithms\n", @@ -132,7 +131,7 @@ { "cell_type": "code", "execution_count": 5, - "id": "fd1290f1", + "id": "6839d8ad", "metadata": {}, "outputs": [ { @@ -144,14 +143,14 @@ } ], "source": [ - "from pytorch_lightning.utilities.seed import seed_everything\n", + "from pytorch_lightning import seed_everything\n", "seed_everything(0, workers=True)\n", "torch.use_deterministic_algorithms(True, warn_only=True)\n" ] }, { "cell_type": "markdown", - "id": "f29a6c10", + "id": "1f1490e7", "metadata": {}, "source": [ "We will use several datasets shipped with `torchvision` for our\n", @@ -162,12 +161,13 @@ { "cell_type": "code", "execution_count": 6, - "id": "c85308d1", + "id": "07dba2dd", "metadata": { "lines_to_next_cell": 0 }, "outputs": [], "source": [ + "from torchvision.io import read_image\n", "from torchvision.datasets import MNIST, CIFAR100\n", "from torchvision.models import (resnet50,\n", " ResNet50_Weights)\n", @@ -179,7 +179,7 @@ }, { "cell_type": "markdown", - "id": "6ca24f46", + "id": "36ec305c", "metadata": {}, "source": [ "We have provided a few utilities in `ISLP` specifically for this lab.\n", @@ -197,7 +197,7 @@ { "cell_type": "code", "execution_count": 7, - "id": "4de9f03c", + "id": "89763447", "metadata": {}, "outputs": [], "source": [ @@ -209,7 +209,7 @@ }, { "cell_type": "markdown", - "id": "d81a775a", + "id": "dfc13283", "metadata": {}, "source": [ "In addition we have included some helper\n", @@ -226,7 +226,7 @@ { "cell_type": "code", "execution_count": 8, - "id": "4ef95fe3", + "id": "ac5ab1b0", "metadata": {}, "outputs": [], "source": [ @@ -238,7 +238,7 @@ }, { "cell_type": "markdown", - "id": "d8d760ad", + "id": "04f757bd", "metadata": {}, "source": [ "Finally, we introduce some utility imports not directly related to\n", @@ -255,7 +255,7 @@ { "cell_type": "code", "execution_count": 9, - "id": "493821a9", + "id": "5a5468e6", "metadata": { "lines_to_next_cell": 2 }, @@ -267,7 +267,7 @@ }, { "cell_type": "markdown", - "id": "c415e4e5", + "id": "690a5255", "metadata": {}, "source": [ "## Single Layer Network on Hitters Data\n", @@ -277,7 +277,7 @@ { "cell_type": "code", "execution_count": 10, - "id": "a427e224", + "id": "d635398b", "metadata": { "lines_to_next_cell": 0 }, @@ -289,7 +289,7 @@ }, { "cell_type": "markdown", - "id": "f1ca2542", + "id": "a0fd86f3", "metadata": {}, "source": [ " We will fit two linear models (least squares and lasso) and compare their performance\n", @@ -305,7 +305,7 @@ { "cell_type": "code", "execution_count": 11, - "id": "feac4b15", + "id": "2c621749", "metadata": { "lines_to_next_cell": 0 }, @@ -318,7 +318,7 @@ }, { "cell_type": "markdown", - "id": "ad0d90b5", + "id": "f32a66d7", "metadata": {}, "source": [ "The `to_numpy()` method above converts `pandas`\n", @@ -331,7 +331,7 @@ }, { "cell_type": "markdown", - "id": "35acacc2", + "id": "b5565350", "metadata": {}, "source": [ "We now split the data into test and training, fixing the random\n", @@ -341,7 +341,7 @@ { "cell_type": "code", "execution_count": 12, - "id": "6a75a640", + "id": "cd19596a", "metadata": {}, "outputs": [], "source": [ @@ -356,7 +356,7 @@ }, { "cell_type": "markdown", - "id": "edc24bfb", + "id": "b82951aa", "metadata": {}, "source": [ "### Linear Models\n", @@ -366,7 +366,7 @@ { "cell_type": "code", "execution_count": 13, - "id": "32d8de64", + "id": "e4bfcd5a", "metadata": {}, "outputs": [ { @@ -388,7 +388,7 @@ }, { "cell_type": "markdown", - "id": "d60340ef", + "id": "bf3523a8", "metadata": {}, "source": [ "Next we fit the lasso using `sklearn`. We are using\n", @@ -402,7 +402,7 @@ { "cell_type": "code", "execution_count": 14, - "id": "46786db6", + "id": "36f8290b", "metadata": {}, "outputs": [], "source": [ @@ -414,7 +414,7 @@ }, { "cell_type": "markdown", - "id": "e7ff854a", + "id": "9f1bf0ad", "metadata": {}, "source": [ "We need to create a grid of values for $\\lambda$. As is common practice, \n", @@ -425,7 +425,7 @@ { "cell_type": "code", "execution_count": 15, - "id": "2b55b38b", + "id": "5015c394", "metadata": { "lines_to_next_cell": 0 }, @@ -440,7 +440,7 @@ }, { "cell_type": "markdown", - "id": "977dea00", + "id": "89f6b4e4", "metadata": {}, "source": [ "Note that we had to transform the data first, since the scale of the variables impacts the choice of $\\lambda$.\n", @@ -450,7 +450,7 @@ { "cell_type": "code", "execution_count": 16, - "id": "cc44c559", + "id": "b5dc7d68", "metadata": {}, "outputs": [], "source": [ @@ -466,7 +466,7 @@ }, { "cell_type": "markdown", - "id": "fca88ebb", + "id": "0b64a882", "metadata": {}, "source": [ "We extract the lasso model with best cross-validated mean absolute error, and evaluate its\n", @@ -477,7 +477,7 @@ { "cell_type": "code", "execution_count": 17, - "id": "1bd1fd13", + "id": "2c49196f", "metadata": { "lines_to_next_cell": 0 }, @@ -501,7 +501,7 @@ }, { "cell_type": "markdown", - "id": "f19cd1f2", + "id": "61f016c9", "metadata": {}, "source": [ "This is similar to the results we got for the linear model fit by least squares. However, these results can vary a lot for different train/test splits; we encourage the reader to try a different seed in code block 12 and rerun the subsequent code up to this point.\n", @@ -519,7 +519,7 @@ { "cell_type": "code", "execution_count": 18, - "id": "4b2ccc5a", + "id": "df5864e2", "metadata": {}, "outputs": [], "source": [ @@ -541,7 +541,7 @@ }, { "cell_type": "markdown", - "id": "5da217b2", + "id": "4b05cc28", "metadata": {}, "source": [ "The `class` statement identifies the code chunk as a\n", @@ -577,7 +577,7 @@ { "cell_type": "code", "execution_count": 19, - "id": "108ad1f1", + "id": "da601fe1", "metadata": {}, "outputs": [], "source": [ @@ -586,7 +586,7 @@ }, { "cell_type": "markdown", - "id": "46d750dd", + "id": "326f3b54", "metadata": {}, "source": [ "The object `self.sequential` is a composition of four maps. The\n", @@ -601,7 +601,7 @@ }, { "cell_type": "markdown", - "id": "e0c250c5", + "id": "a246aedb", "metadata": {}, "source": [ "The package `torchinfo` provides a `summary()` function that neatly summarizes\n", @@ -612,21 +612,11 @@ { "cell_type": "code", "execution_count": 20, - "id": "2f20059e", + "id": "15dd23a9", "metadata": { "lines_to_next_cell": 0 }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -644,7 +634,7 @@ "Total params: 1,051\n", "Trainable params: 1,051\n", "Non-trainable params: 0\n", - "Total mult-adds (M): 0.18\n", + "Total mult-adds (Units.MEGABYTES): 0.18\n", "===================================================================================================================\n", "Input size (MB): 0.01\n", "Forward/backward pass size (MB): 0.07\n", @@ -668,7 +658,7 @@ }, { "cell_type": "markdown", - "id": "05a0eb81", + "id": "3cb4b8bc", "metadata": {}, "source": [ "We have truncated the end of the output slightly, here and in subsequent uses.\n", @@ -690,7 +680,7 @@ { "cell_type": "code", "execution_count": 21, - "id": "6ca3030d", + "id": "dae83bc5", "metadata": { "lines_to_next_cell": 0 }, @@ -703,7 +693,7 @@ }, { "cell_type": "markdown", - "id": "7924f53d", + "id": "80475fa2", "metadata": {}, "source": [ "We do the same for the test data." @@ -712,7 +702,7 @@ { "cell_type": "code", "execution_count": 22, - "id": "86723b3e", + "id": "81e217a8", "metadata": {}, "outputs": [], "source": [ @@ -723,7 +713,7 @@ }, { "cell_type": "markdown", - "id": "0d055846", + "id": "7f49263d", "metadata": {}, "source": [ "Finally, this dataset is passed to a `DataLoader()` which ultimately\n", @@ -747,7 +737,7 @@ { "cell_type": "code", "execution_count": 23, - "id": "999279fd", + "id": "e5359e31", "metadata": {}, "outputs": [], "source": [ @@ -756,7 +746,7 @@ }, { "cell_type": "markdown", - "id": "9fe60b31", + "id": "105b015f", "metadata": {}, "source": [ "The general training setup in `pytorch_lightning` involves\n", @@ -779,7 +769,7 @@ { "cell_type": "code", "execution_count": 24, - "id": "7bd9cc5c", + "id": "7a19d6d8", "metadata": {}, "outputs": [], "source": [ @@ -792,7 +782,7 @@ }, { "cell_type": "markdown", - "id": "9be1f578", + "id": "8d1f2a76", "metadata": {}, "source": [ "Next we must provide a `pytorch_lightning` module that controls\n", @@ -807,7 +797,7 @@ { "cell_type": "code", "execution_count": 25, - "id": "5be2f822", + "id": "07bc10ef", "metadata": {}, "outputs": [], "source": [ @@ -817,7 +807,7 @@ }, { "cell_type": "markdown", - "id": "78e707d8", + "id": "1ebf9835", "metadata": {}, "source": [ " By using the `SimpleModule.regression()` method, we indicate that we will use squared-error loss as in\n", @@ -834,7 +824,7 @@ { "cell_type": "code", "execution_count": 26, - "id": "87334d33", + "id": "08c71fb4", "metadata": {}, "outputs": [], "source": [ @@ -843,7 +833,7 @@ }, { "cell_type": "markdown", - "id": "07663639", + "id": "511617c3", "metadata": {}, "source": [ "Finally we are ready to train our model and log the results. We\n", @@ -865,7 +855,7 @@ { "cell_type": "code", "execution_count": 27, - "id": "1a474999", + "id": "81a8c626", "metadata": { "lines_to_next_cell": 0 }, @@ -874,12 +864,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:1789: UserWarning: MPS available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='mps', devices=1)`.\n", - " rank_zero_warn(\n", "\n", " | Name | Type | Params\n", "---------------------------------------\n", @@ -909,7 +897,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7f1f820ee6fa4d81a3736b68611f3bac", + "model_id": "ef89ad488fd24d7a8ab978b4d3f22ca1", "version_major": 2, "version_minor": 0 }, @@ -1550,20 +1538,81 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d44f77bd4233488ebe5c4d84b948f780", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "277ab0a6550f47a587371058c876ce69", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "778d348b298f403fb26acfd4daf7ca04", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" + "`Trainer.fit` stopped: `max_epochs=50` reached.\n" ] } ], @@ -1578,7 +1627,7 @@ }, { "cell_type": "markdown", - "id": "5e154e47", + "id": "abe1a22c", "metadata": {}, "source": [ "At each step of SGD, the algorithm randomly selects 32 training observations for\n", @@ -1594,7 +1643,7 @@ { "cell_type": "code", "execution_count": 28, - "id": "e3b24643", + "id": "083670c6", "metadata": { "lines_to_next_cell": 2 }, @@ -1602,7 +1651,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ce9e57deabef4f55aba22efb507872f1", + "model_id": "c22d1cd8cde040988ca2a2718541d22b", "version_major": 2, "version_minor": 0 }, @@ -1614,21 +1663,34 @@ "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_loss 103304.8515625\n", - " test_mae 224.26962280273438\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - ] + "data": { + "text/html": [ + "
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We can find the\n", @@ -1658,7 +1720,7 @@ { "cell_type": "code", "execution_count": 29, - "id": "f9b266e7", + "id": "02ba9edf", "metadata": {}, "outputs": [], "source": [ @@ -1667,7 +1729,7 @@ }, { "cell_type": "markdown", - "id": "b7ff26d7", + "id": "daf8ed8d", "metadata": {}, "source": [ "Since we will produce similar plots in later examples, we write a\n", @@ -1677,7 +1739,7 @@ { "cell_type": "code", "execution_count": 30, - "id": "c5752a0b", + "id": "4184557c", "metadata": { "lines_to_next_cell": 0 }, @@ -1711,7 +1773,7 @@ }, { "cell_type": "markdown", - "id": "874c2611", + "id": "026c1c4d", "metadata": {}, "source": [ "We now set up our axes, and use our function to produce the MAE plot." @@ -1720,14 +1782,14 @@ { "cell_type": "code", "execution_count": 31, - "id": "ff0c9fa0", + "id": "3244deeb", "metadata": { "lines_to_next_cell": 2 }, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1749,7 +1811,7 @@ }, { "cell_type": "markdown", - "id": "212c64a3", + "id": "670a3e8f", "metadata": {}, "source": [ "We can predict directly from the final model, and\n", @@ -1767,7 +1829,7 @@ { "cell_type": "code", "execution_count": 32, - "id": "1ee2b61b", + "id": "36bb545e", "metadata": { "lines_to_next_cell": 0 }, @@ -1775,7 +1837,7 @@ { "data": { "text/plain": [ - "tensor(224.2696, grad_fn=)" + "tensor(250.8108, grad_fn=)" ] }, "execution_count": 32, @@ -1791,7 +1853,7 @@ }, { "cell_type": "markdown", - "id": "8140eb0d", + "id": "ae4b9ca6", "metadata": {}, "source": [ " " @@ -1799,20 +1861,21 @@ }, { "cell_type": "markdown", - "id": "64fa7609", + "id": "b8b7fd3c", "metadata": {}, "source": [ "### Cleanup\n", "In setting up our data module, we had initiated\n", "several worker processes that will remain running.\n", "We delete all references to the torch objects to ensure these processes\n", - "will be killed." + "will be killed.\n", + " " ] }, { "cell_type": "code", "execution_count": 33, - "id": "0ca069a3", + "id": "00371f48", "metadata": { "lines_to_next_cell": 2 }, @@ -1831,7 +1894,7 @@ }, { "cell_type": "markdown", - "id": "ac321b7f", + "id": "5707d61c", "metadata": {}, "source": [ "## Multilayer Network on the MNIST Digit Data\n", @@ -1845,7 +1908,7 @@ { "cell_type": "code", "execution_count": 34, - "id": "af6a0a33", + "id": "3e28d6ba", "metadata": {}, "outputs": [ { @@ -1876,7 +1939,7 @@ }, { "cell_type": "markdown", - "id": "6c8aa040", + "id": "eb8b7e29", "metadata": {}, "source": [ "There are 60,000 images in the training data and 10,000 in the test\n", @@ -1900,7 +1963,7 @@ { "cell_type": "code", "execution_count": 35, - "id": "0df8a0c8", + "id": "cb04829e", "metadata": {}, "outputs": [], "source": [ @@ -1913,7 +1976,7 @@ }, { "cell_type": "markdown", - "id": "3dc50b18", + "id": "1119e22a", "metadata": {}, "source": [ "Let’s take a look at the data that will get fed into our network. We loop through the first few\n", @@ -1923,7 +1986,7 @@ { "cell_type": "code", "execution_count": 36, - "id": "0c7dd6ee", + "id": "c4a265fc", "metadata": { "lines_to_next_cell": 2 }, @@ -1949,7 +2012,7 @@ }, { "cell_type": "markdown", - "id": "cc80f21e", + "id": "f65ada90", "metadata": {}, "source": [ "We see that the $X$ for each batch consists of 256 images of size `1x28x28`.\n", @@ -1962,7 +2025,7 @@ { "cell_type": "code", "execution_count": 37, - "id": "63e48c70", + "id": "60339a03", "metadata": {}, "outputs": [], "source": [ @@ -1988,7 +2051,7 @@ }, { "cell_type": "markdown", - "id": "d5a5ffef", + "id": "5b8f87da", "metadata": {}, "source": [ "We see that in the first layer, each `1x28x28` image is flattened, then mapped to\n", @@ -2002,7 +2065,7 @@ { "cell_type": "code", "execution_count": 38, - "id": "92405826", + "id": "1d0f24b2", "metadata": {}, "outputs": [], "source": [ @@ -2011,7 +2074,7 @@ }, { "cell_type": "markdown", - "id": "b16bd23a", + "id": "0ee4771e", "metadata": {}, "source": [ "We can check that the model produces output of expected size based\n", @@ -2021,7 +2084,7 @@ { "cell_type": "code", "execution_count": 39, - "id": "2c8f7a48", + "id": "42a4931b", "metadata": {}, "outputs": [ { @@ -2041,7 +2104,7 @@ }, { "cell_type": "markdown", - "id": "da0de828", + "id": "628d56f9", "metadata": {}, "source": [ "Let’s take a look at the summary of the model. Instead of an `input_size` we can pass\n", @@ -2052,19 +2115,9 @@ { "cell_type": "code", "execution_count": 40, - "id": "9f502df8", + "id": "69e62d88", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -2087,7 +2140,7 @@ "Total params: 235,146\n", "Trainable params: 235,146\n", "Non-trainable params: 0\n", - "Total mult-adds (M): 60.20\n", + "Total mult-adds (Units.MEGABYTES): 60.20\n", "===================================================================================================================\n", "Input size (MB): 0.80\n", "Forward/backward pass size (MB): 0.81\n", @@ -2111,29 +2164,31 @@ }, { "cell_type": "markdown", - "id": "f98b70bb", + "id": "f8e77337", "metadata": {}, "source": [ "Having set up both the model and the data module, fitting this model is\n", "now almost identical to the `Hitters` example. In contrast to our regression model, here we will use the\n", "`SimpleModule.classification()` method which\n", - "uses the cross-entropy loss function instead of mean squared error." + "uses the cross-entropy loss function instead of mean squared error. It must be supplied with the number of\n", + "classes in the problem." ] }, { "cell_type": "code", "execution_count": 41, - "id": "d1a7590f", + "id": "2027a378", "metadata": {}, "outputs": [], "source": [ - "mnist_module = SimpleModule.classification(mnist_model)\n", + "mnist_module = SimpleModule.classification(mnist_model,\n", + " num_classes=10)\n", "mnist_logger = CSVLogger('logs', name='MNIST')\n" ] }, { "cell_type": "markdown", - "id": "ca665912", + "id": "9146b9b5", "metadata": {}, "source": [ "Now we are ready to go. The final step is to supply training data, and fit the model." @@ -2142,7 +2197,7 @@ { "cell_type": "code", "execution_count": 42, - "id": "e2fe6de3", + "id": "4a5e941d", "metadata": { "lines_to_next_cell": 0 }, @@ -2151,12 +2206,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:1789: UserWarning: MPS available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='mps', devices=1)`.\n", - " rank_zero_warn(\n", "\n", " | Name | Type | Params\n", "-------------------------------------------\n", @@ -2186,7 +2239,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "82f9178e94874e7e9cbb3b27cc1c351f", + "model_id": "003350959546477780d1c2c8480ac50e", "version_major": 2, "version_minor": 0 }, @@ -2636,7 +2689,7 @@ }, { "cell_type": "markdown", - "id": "6b4a4e0c", + "id": "8099bdc9", "metadata": {}, "source": [ "We have suppressed the output here, which is a progress report on the\n", @@ -2654,7 +2707,7 @@ }, { "cell_type": "markdown", - "id": "25528d72", + "id": "d6c3bbbc", "metadata": {}, "source": [ "`SimpleModule.classification()` includes\n", @@ -2667,14 +2720,14 @@ { "cell_type": "code", "execution_count": 43, - "id": "73755987", + "id": "603a278a", "metadata": { "lines_to_next_cell": 0 }, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -2697,7 +2750,7 @@ }, { "cell_type": "markdown", - "id": "ba63a8da", + "id": "654cec05", "metadata": {}, "source": [ "Once again we evaluate the accuracy using the `test()` method of our trainer. This model achieves\n", @@ -2707,13 +2760,13 @@ { "cell_type": "code", "execution_count": 44, - "id": "f5269c40", + "id": "93dc968b", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b584fa2b09df4c20939181c016e85bc5", + "model_id": "b16d542a27f64cb187d24b941a7f8e96", "version_major": 2, "version_minor": 0 }, @@ -2725,21 +2778,34 @@ "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_accuracy 0.9681000113487244\n", - " test_loss 0.14706705510616302\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - ] + "data": { + "text/html": [ + "
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+       "┃   Runningstage.testing    ┃                           ┃\n",
+       "┃          metric           ┃       DataLoader 0        ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
+       "│       test_accuracy       │    0.9656999707221985     │\n",
+       "│         test_loss         │    0.15191325545310974    │\n",
+       "└───────────────────────────┴───────────────────────────┘\n",
+       "
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Set `accelerator` and `devices` using `Trainer(accelerator='mps', devices=1)`.\n", - " rank_zero_warn(\n", + "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/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", "-------------------------------------------\n", @@ -2832,7 +2899,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "02fd79458dc34808bb403f8b8475a62d", + "model_id": "b5f0bb1fbf824a808eef2d101e91a0ad", "version_major": 2, "version_minor": 0 }, @@ -2930,7 +2997,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "9c827fce3589462294778b990fc78f2f", + "model_id": "", "version_major": 2, "version_minor": 0 }, @@ -2942,20 +3009,32 @@ "output_type": "display_data" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { @@ -2999,36 +3078,6 @@ "metadata": {}, "output_type": "display_data" }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "a9fcb28681b34dc6921cad2630ca648f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Validation: 0it [00:00, ?it/s]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { @@ -3071,36 +3120,6 @@ "metadata": {}, "output_type": "display_data" }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "e2dd237b55d14ad4a871888e4ecde25d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Validation: 0it [00:00, ?it/s]" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] - }, { "data": { "application/vnd.jupyter.widget-view+json": { @@ -3230,7 +3249,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5d8dc977673646d9ad09d0c5b7e4903a", + "model_id": "", "version_major": 2, "version_minor": 0 }, @@ -3242,20 +3261,32 @@ "output_type": "display_data" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { @@ -3316,7 +3347,7 @@ }, { "cell_type": "markdown", - "id": "c376e402", + "id": "f84cfa36", "metadata": {}, "source": [ "We fit the model just as before and compute the test results." @@ -3325,7 +3356,7 @@ { "cell_type": "code", "execution_count": 47, - "id": "c0bd63e3", + "id": "acb6f88d", "metadata": { "lines_to_next_cell": 0 }, @@ -3333,7 +3364,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "92b4035b1656456d88d929aac0d46d71", + "model_id": "30f89591c26d4f9d9d49d589c36baf06", "version_major": 2, "version_minor": 0 }, @@ -3345,21 +3376,34 @@ "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_accuracy 0.9240999817848206\n", - " test_loss 0.3186827003955841\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - 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+       "│       test_accuracy       │    0.9235000014305115     │\n",
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The example below also illustrates\n", + "Figure 10.5 on page 164. The example below also illustrates\n", "that `TensorDataset` objects can be indexed with integers --- we are choosing\n", "random images from the training data by indexing `cifar_train`. In order to display correctly,\n", "we must reorder the dimensions by a call to `np.transpose()`." @@ -3534,7 +3578,7 @@ { "cell_type": "code", "execution_count": 53, - "id": "94885e68", + "id": "c626e0ff", "metadata": { "lines_to_next_cell": 0 }, @@ -3567,7 +3611,7 @@ }, { "cell_type": "markdown", - "id": "04fda6b8", + "id": "2a1c4832", "metadata": {}, "source": [ "Here the `imshow()` method recognizes from the shape of its argument that it is a 3-dimensional array, with the last dimension indexing the three RGB color channels.\n", @@ -3584,7 +3628,7 @@ { "cell_type": "code", "execution_count": 54, - "id": "cdc2528a", + "id": "9d5bcdf3", "metadata": {}, "outputs": [], "source": [ @@ -3608,7 +3652,7 @@ }, { "cell_type": "markdown", - "id": "31891282", + "id": "a7204121", "metadata": {}, "source": [ "Notice that we used the `padding = \"same\"` argument to\n", @@ -3629,7 +3673,7 @@ { "cell_type": "code", "execution_count": 55, - "id": "845be1ae", + "id": "3e13e9bc", "metadata": {}, "outputs": [], "source": [ @@ -3656,7 +3700,7 @@ }, { "cell_type": "markdown", - "id": "1ed2c036", + "id": "1b07fb1a", "metadata": {}, "source": [ "We build the model and look at the summary. (We had created examples of `X_` earlier.)" @@ -3665,21 +3709,11 @@ { "cell_type": "code", "execution_count": 56, - "id": "be768cbb", + "id": "15c4a382", "metadata": { "lines_to_next_cell": 2 }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -3713,7 +3747,7 @@ "Total params: 964,516\n", "Trainable params: 964,516\n", "Non-trainable params: 0\n", - "Total mult-adds (G): 2.01\n", + "Total mult-adds (Units.GIGABYTES): 2.01\n", "===================================================================================================================\n", "Input size (MB): 1.57\n", "Forward/backward pass size (MB): 63.54\n", @@ -3738,7 +3772,7 @@ }, { "cell_type": "markdown", - "id": "6320d294", + "id": "b168c198", "metadata": {}, "source": [ "The total number of trainable parameters is 964,516.\n", @@ -3766,19 +3800,19 @@ "We saw earlier that entries of a module’s parameters are tensors. In passing\n", "the parameters to the optimizer we are doing more than\n", "simply passing arrays; part of the structure of the graph\n", - "is encoded in the tensors themselves.\n", - " " + "is encoded in the tensors themselves." ] }, { "cell_type": "code", "execution_count": 57, - "id": "67e3e2d9", + "id": "4a40238a", "metadata": {}, "outputs": [], "source": [ "cifar_optimizer = RMSprop(cifar_model.parameters(), lr=0.001)\n", "cifar_module = SimpleModule.classification(cifar_model,\n", + " num_classes=100,\n", " optimizer=cifar_optimizer)\n", "cifar_logger = CSVLogger('logs', name='CIFAR100')\n" ] @@ -3786,14 +3820,14 @@ { "cell_type": "code", "execution_count": 58, - "id": "1ea339ff", + "id": "8aab2c62", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", @@ -3826,7 +3860,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fdb66e85a34e49afafdf51191e247d54", + "model_id": "08572337f9c44ae08b65fca1a08db4ce", "version_major": 2, "version_minor": 0 }, @@ -4276,10 +4310,10 @@ }, { "cell_type": "markdown", - "id": "977e27d9", + "id": "090f6400", "metadata": {}, "source": [ - "This model takes 10 minutes or more to run and achieves about 42% accuracy on the test\n", + "This model can take 10 minutes or more to run and achieves about 42% accuracy on the test\n", "data. Although this is not terrible for 100-class data (a random\n", "classifier gets 1% accuracy), searching the web we see results around\n", "75%. Typically it takes a lot of architecture carpentry,\n", @@ -4292,14 +4326,14 @@ { "cell_type": "code", "execution_count": 59, - "id": "0a9068d9", + "id": "12474ef6", "metadata": { "lines_to_next_cell": 0 }, "outputs": [ { "data": { - "image/png": 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", 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q2LGj5syZo48//lgFBQW67bbbdN1119U9HoklAgYAIHYyM6Uvv5QKCqTVqz3fS0oiGi68brrpJv3zn//UxIkT6+ZM3HvvvTrvvPM0ceJEjRs3TqmpqZo6dWrA75mQkKCNGzfqu+++06hRo/STn/xEDz30kE+fH/3oR7rjjjt06623aujQoXr77be1ePFinz7Tpk3TFVdcofHjx6tnz55+l8omJSXpL3/5i7755huNHDlSWVlZuvTSS7VixYrg/zIiwLCsABcPtxJVVVVKTk5WZWVl0BNqAAAe33//vUpKStSvXz917Ngx1sOBjZr6bxvMNZQ7GAAAwHYEDAAAYDsCBgAAsB0BAwAA2I6AAQAIWRtbJ9Am2PXflIABAAiatzrk0aNHYzwS2M1bUdQRZpEz9iIBAATN4XDo1FNP1f79+yV5ajIYQZbrRstTW1urAwcOKCkpSe3ahRcRCBgAgJCkpqZKUl3IQOuQkJCg008/PezASMAAAITEMAylpaWpV69eOnbsWKyHA5t06NBBCQnhz6AgYAAAwuJwOMJ+Xo/Wh0meAADAdgQMAABgOwIGAACwHQEDAADYjoABAABsR8AAAAC2I2AAAADbETAAAIDtCBgAAMB2BAwAAGA7AgYAALAdAQMAANiOgAEAAGxHwAAAALYjYAAAANsRMAAAgO0IGAAAwHYEDAAAYDsCBgAAsB0BAwAA2I6AAQAAbEfAAAAAtiNgAAAA2xEwAACA7QgYAADAdgQMAABgOwIGAACwHQEDAADYjoABAABsR8AAAAC2I2AAAADbETAAAIDtYh4wnnzySaWnp6tjx44aPXq03nvvvSb75+bm6swzz1SnTp3kcrl0xx136Pvvv4/SaAEAQCBiGjDWrVun+fPna8mSJdqxY4eGDBmiiRMnav/+/X77r169WnfffbeWLFmiTz/9VM8995zWrVune+65J8ojBwAATYlpwHjiiSd0880364YbbtDZZ5+tp59+WklJSXr++ef99n/77bd1wQUXaObMmUpPT9fll1+uGTNmNHvXAwAARFfMAkZNTY0++OADTZgw4V+DSUjQhAkTtG3bNr/HjB07Vh988EFdoPjiiy/06quvatKkSY2ep7q6WlVVVT5fAAAgstrF6sQHDx6UaZpKSUnxaU9JSdHu3bv9HjNz5kwdPHhQF154oSzL0vHjx/Wzn/2syUcky5Yt09KlS20dOwAAaFrMJ3kGo7CwUA8//LB++9vfaseOHXK73XrllVf04IMPNnrMwoULVVlZWfdVWloaxREDANA2xewORo8ePeRwOLRv3z6f9n379ik1NdXvMYsXL9Z1112nn/zkJ5KkwYMH68iRI5o7d64WLVqkhISGeSkxMVGJiYn2fwAAANComN3B6NChg4YPH64tW7bUtdXW1mrLli0aM2aM32OOHj3aIEQ4HA5JkmVZkRssAAAISszuYEjS/PnzNWfOHI0YMUKjRo1Sbm6ujhw5ohtuuEGSNHv2bPXp00fLli2TJE2ePFlPPPGEhg0bptGjR+uzzz7T4sWLNXny5LqgAQAAYi+mAWP69Ok6cOCA7rvvPlVUVGjo0KHatGlT3cTPvXv3+tyxuPfee2UYhu69916VlZWpZ8+emjx5sh566KFYfQQAAOCHYbWxZwtVVVVKTk5WZWWlunbtGuvhAAAQN4K5hsbVKhIAABAfCBgAAMB2BAwAAGA7AgYAALAdAQMAANiOgAEAAGxHwAAAALYjYAAAANsRMAAAgO0IGAAAwHYEDAAAYDsCBgAAsB0BAwAA2I6AAQAAbEfAAAAAtiNgAAAA2xEwAACA7QgYAADAdgQMAABgOwIGAACwHQEDAADYjoABAABsR8AAAAC2I2AAAADbETAAAIDtCBgAAMB2BAwAAGA7AgYAALAdAQMAANiOgAEAAGxHwAAAALYjYAAAANsRMAAAgO0IGAAAwHYEDAAAYDsCBgAAsB0BAwAA2I6AAQAAbEfAAAAAtiNgAAAA2xEwAACA7QgYAADAdgQMAABgOwIGAACwHQEDAADYjoABAABsR8AAAAC2I2AAAADbETAAAIDtCBgAAMB2BAwAAGA7AgYAALAdAQMAANiOgAEAAGxHwAAAALYjYAAAANsRMAAAgO0IGAAAwHYEDAAAYDsCBgAAsB0BAwAA2I6AAQAAbEfAAAAAtiNgAAAA2xEwAACA7drFegAAAMBepmmqqKhI5eXlSktLU0ZGhhwOR1THQMAAAKAVcbvdys7O1ldffVXX5nQ6lZeXp8zMzKiNg0ckAAC0Em63W1lZWT7hQpLKysqUlZUlt9sdtbEQMAAAaAVM01R2drYsy2rwM29bTk6OTNOMyngIGAAAtFCmaaqwsFBr1qxRYWFhk+GgqKiowZ2Lk1mWpdLSUhUVFUViqA0wBwMAgBYo2LkU5eXlAb1voP3CxR0MAABamFDmUqSlpQX03oH2C5dh+XtY04pVVVUpOTlZlZWV6tq1a6yHAwCAD9M0lZ6e3ujjDsMw5HQ6VVJS4rP01HtcWVmZ33kYjR0XjGCuodzBAACgBQl1LoXD4VBeXp4kT5g4mfd1bm5u1OphEDAAAGhBwplLkZmZqfz8fPXp08en3el0Kj8/P6p1MJjkCQBABAVbVTPcuRSZmZmaMmVKzCt5MgcDAIAICaWqZjTmUoSKORgAAMRYqFU1W9pcilARMAAAaEYwBa+8/cOpqtmS5lKEikckAAA0IZTHHIWFhRo/fnyz711QUKBx48Y1+vOWsCvqyYK5hjLJEwCARngfc9T/t7j3MUdjdxPsqqrpcDiaDCAtGY9IAABtRjCPOsJ5zNHSqmrGQswDxpNPPqn09HR17NhRo0eP1nvvvddk/2+//Vbz5s1TWlqaEhMT9YMf/ECvvvpqlEYLAIhXbrdb6enpGj9+vGbOnKnx48crPT290cmW4WwelpGRIafT2WCSppdhGHK5XMrIyAjtw8SBmAaMdevWaf78+VqyZIl27NihIUOGaOLEidq/f7/f/jU1Nbrsssv05ZdfKj8/X3v27NGzzz7bYBIMAAAnC2VFRziPOVrLSpCwWDE0atQoa968eXWvTdO0evfubS1btsxv/6eeesrq37+/VVNTE/I5KysrLUlWZWVlyO8BAIgfx48ft5xOpyXJ75dhGJbL5bKOHz/uc1xBQUGjx5z8VVBQ0Oi5N2zY0ODcLpfL2rBhQ4Q/dWQEcw2N2SqSmpoaJSUlKT8/X1OnTq1rnzNnjr799lu99NJLDY6ZNGmSTjvtNCUlJemll15Sz549NXPmTC1YsKDRFFhdXa3q6uq611VVVXK5XKwiAYA2ItQVHXYVvGppK0HCERerSA4ePCjTNJWSkuLTnpKSot27d/s95osvvtBf//pXzZo1S6+++qo+++wz3XLLLTp27JiWLFni95hly5Zp6dKlto8fABAfQn3U4X3MkZWVJcMwfEJGMI854nklSDhiPskzGLW1terVq5eeeeYZDR8+XNOnT9eiRYv09NNPN3rMwoULVVlZWfdVWloaxREDAGItnBUdraHgVazE7A5Gjx495HA4tG/fPp/2ffv2KTU11e8xaWlpat++vU9aHDRokCoqKlRTU6MOHTo0OCYxMVGJiYn2Dh4AEDPBPnLwruho7lFHYys6WsrmYfEmZncwOnTooOHDh2vLli11bbW1tdqyZYvGjBnj95gLLrhAn332mWpra+va/va3vyktLc1vuAAAtC7BLjWV7FnR4X3MMWPGDI0bN45wEYjIzjdt2tq1a63ExERr1apV1ieffGLNnTvXOvXUU62KigrLsizruuuus+6+++66/nv37rW6dOli3XrrrdaePXusP//5z1avXr2sX/ziFwGfk1UkABCfNmzYYBmG4XcViGEYza7MaG0rOmIhLlaReK1YsUKPPfaYKioqNHToUC1fvlyjR4+WJI0bN07p6elatWpVXf9t27bpjjvuUHFxsfr06aObbrqpyVUk9bEXCQDEH++KjsYKX7XFFR2xEMw1NOYBI9oIGAAQf+zaPAzhCeYaGlerSAAAbZNdm4chethNFQAQE8E8rmDzsPjDHQwAQNQFuxqEzcPiDwEDABBVoWw8xuZh8YeAAQCIGtM0lZ2d7bfglbctJydHpmk2+DlVNeMLq0gAACELdtmnHatBWGoaO3Gx2RkAIL653W5lZ2f7POpwOp3Ky8tr9G6CHatB2urmYfGGRyQAgKCFMo9CYjVIW8IjEgBAUMKpquk9trmNx5qryInYoNAWACAopmmqsLBQa9asUWFhod9Jll5FRUWNhgvJM1mztLRURUVFDX7GapC2I+iAkZ6ergceeEB79+6NxHgAAFEWbE2KcOdRsBqkbQg6YOTk5Mjtdqt///667LLLtHbtWlVXV0dibACACAtlLoUd8ygyMzP15ZdfqqCgQKtXr1ZBQYFKSkoIF61IyHMwduzYoVWrVmnNmjUyTVMzZ87UjTfeqPPOO8/uMdqKORgA4BHqXArmUbRdUZmDcd5552n58uX6+uuvtWTJEv3ud7/TyJEjNXToUD3//PN+f+kAAC1HqHMpmEeBQIQcMI4dO6YXXnhBP/rRj/Sf//mfGjFihH73u99p2rRpuueeezRr1iw7xwkAsFk4cymYR4HmBF1oa8eOHVq5cqXWrFmjhIQEzZ49W7/+9a911lln1fW5+uqrNXLkSFsHCgCwV7hzKTIzMzVlyhSqasKvoAPGyJEjddlll+mpp57S1KlT1b59+wZ9+vXrp2uvvdaWAQIAAhNsCW3vDqXNzaVoaodSqmqiMUEHjC+++EJ9+/Ztsk/nzp21cuXKkAcFAAhOKGW7vXMpsrKyZBiGT8hgLgXCFfQcjP379+vdd99t0P7uu+/q/ffft2VQAIDAhVq2W2IuBSIn6GWqo0aN0l133aWsrCyfdrfbrUceecRv+GhJWKYKoDUJp2x3/fdhLgWaE9HdVD/55BO/tS6GDRumTz75JNi3AwCEIZilpk3NlWAuBewW9COSxMRE7du3r0F7eXm52rVj93cAiCY7tj8HIiHogHH55Zdr4cKFqqysrGv79ttvdc899+iyyy6zdXAAgKax/TlaqqDnYJSVlemiiy7SP/7xDw0bNkySVFxcrJSUFG3evFkulysiA7ULczAAtGTBzoWgbDeiKaKlwvv06aOPPvpIjz76qM4++2wNHz5ceXl52rVrV4sPFwDQkgW7q6lE2W60XCFvdhavuIMBoCXyLjWt/3/J3pDQ3JJRf3UwXC6XcnNzWWoK2wRzDQ05YHzyySfau3evampqfNp/9KMfhfJ2UUPAANDSsNQU8SKiy1S/+OILXX311dq1a5dP5TdvyjZNM4QhA0DrEszFnqWmaI2CnoORnZ2tfv36af/+/UpKStL//u//auvWrRoxYoQKCwsjMEQAiC/BzqVgqSlao6ADxrZt2/TAAw+oR48eSkhIUEJCgi688EItW7ZMt99+eyTGCABxI5Sy3Sw1RWsUdMAwTVNdunSRJPXo0UNff/21JKlv377as2ePvaMDgDhimqays7P9Lhf1tuXk5DR4lOzd1bT+KhAvwzDkcrma3NUUaGmCDhjnnHOOdu7cKUkaPXq0Hn30Ub311lt64IEH1L9/f9sHCADxIpi5FCdjqSlao6ADxr333qva2lpJ0gMPPKCSkhJlZGTo1Vdf1fLly20fIADEi3DmUrCrKVqboFeRTJw4se7PZ5xxhnbv3q1vvvlG3bp1a/T2HgC0BeHOpcjMzNSUKVNYaopWIag6GMeOHVOnTp1UXFysc845J5LjihjqYACIFMp2o7WLWKnw9u3b6/TTT6fWBYA2wTRNFRYWas2aNSosLGz2//uYSwH8S9BzMBYtWqR77rlH33zzTSTGAwAtQij7gkjMpQC8gi4VPmzYMH322Wc6duyY+vbtq86dO/v8fMeOHbYO0G48IgHQnHD3BZEo243WKaKlwqdOnRrquACgxWuuloVhGMrJydGUKVOaDAyU7UZbF3TAWLJkSSTGAQAtgl37ggBtXdBzMACgNWNfEMAeQd/BSEhIaLLeBStMALQ0wcyHYF8QwB5BB4yNGzf6vD527Jg+/PBD/f73v9fSpUttGxgA2MHtdis7O9vnsYfT6VReXp7fiZrefUGaq2XBviBA04JeRdKY1atXa926dXrppZfseLuIYRUJ0HaEuhrEe5wkn2ODWUUCtEYRK7TVlPPPP19btmyx6+0AICyh7mwqUcsCsEPQj0j8+e6777R8+fIG/2MEgFgJdzUI+4IA4Qk6YNTf1MyyLB06dEhJSUn67//+b1sHBwBewRausmM1CLUsgNAFHTB+/etf+wSMhIQE9ezZU6NHj1a3bt1sHRwASMFP1JRYDQLEmm2TPOMFkzyB+BLqRE12NgXsF9FJnitXrtT69esbtK9fv16///3vg307AGhUOBM12dkUiK2gA8ayZcvUo0ePBu29evXSww8/bMugAEAKbqKmP6wGAWIn6DkYe/fuVb9+/Rq09+3bV3v37rVlUAAg2TNRk9UgQGwEHTB69eqljz76SOnp6T7tO3fuVPfu3e0aFwDYNlGT1SBA9AX9iGTGjBm6/fbbVVBQINM0ZZqm/vrXvyo7O1vXXnttJMYIoI3ylu1ubP8jwzDkcrko2w20QEHfwXjwwQf15Zdf6tJLL1W7dp7Da2trNXv2bOZgAGhSsLUsvBM1s7KyZBiG37LdTNQEWqaQl6n+/e9/V3FxsTp16qTBgwerb9++do8tIlimCsRGKLUsmjrW5XIpNzeXiZpAFAVzDaUOBoCIC7WWxcmCvfsBwH4RDRjTpk3TqFGjtGDBAp/2Rx99VNu3b/dbI6MlIWAA0eUteNXYclMKXgHxI6KFtrZu3apJkyY1aL/yyiu1devWYN8OQCsXbi0LAPEp6IBx+PBhdejQoUF7+/btVVVVZcugALQedtSyABB/gg4YgwcP1rp16xq0r127VmeffbYtgwLQerDpGNA2Bb1MdfHixcrMzNTnn3+uSy65RJK0ZcsWrV69Wvn5+bYPEEB889ayaG7TMWpZAK1L0HcwJk+erBdffFGfffaZbrnlFv3nf/6nysrK9Ne//lVnnHFGJMYIII6x6RjQNoW9TLWqqkpr1qzRc889pw8++MDvroYtCatIgPCFsmSUWhZA/ItKHYytW7fqueee04YNG9S7d29lZmZq2rRpGjlyZEiDjhYCBhCecApmUcsCiG/BXEODmoNRUVGhVatW6bnnnlNVVZWuueYaVVdX68UXX2SCJ9AGNFYwq6ysTFlZWc0WzGLTMaDtCHgOxuTJk3XmmWfqo48+Um5urr7++mv95je/ieTYALQgpmkqOzvb70RNb1tOTk6Lf0wKIDoCDhivvfaabrrpJi1dulRXXXUVtzWBNoaCWQCCEXDAePPNN3Xo0CENHz5co0eP1ooVK3Tw4MFIjg1AC0LBLNjONKXCQmnNGs/31nr3q618znoCDhjnn3++nn32WZWXl+unP/2p1q5dq969e6u2tlabN2/WoUOHIjlOADFGwSzYyu2W0tOl8eOlmTM939PTPe3NiacLdjifM86FtUx1z549eu655/THP/5R3377rS677DK9/PLLdo7PdqwiAULj3bSsuYJZbFqGZrndUlaWVP/3yFsnJT9famyysNstZWdLJz+uczqlvLzGjzmZaUpFRVJ5uZSWJmVkSJH6fQ3nc4Y73gh9zqCuoZYNjh8/bm3cuNGaPHmyHW8XUZWVlZYkq7KyMtZDAWLq+PHjVkFBgbV69WqroKDAOn78eLPHbNiwwTIMwzIMw5JU9+Vt27BhQxRGjhbl+HHLKiiwrNWrPd+b+z06ftyynE7L8lx2G34ZhmW5XP7fZ8MGz8/9HWMYnp83ZcOGhud2Ops/LhThfM5wxxvBzxnMNdSWgBFPCBiAJyg4nU6fkOB0OgMKCP6OdblchIu2KJQLWUFB4xfdk78KCnyPC/eCHW44CVaonzPc8Ub4cxIwmkDAQFvnvQtxckAI9i5EKHc/0MqEeiFbvTqwC+/q1b7HhXPBtuNuQrBC/ZzhjDcKnzOYa2jQe5EAiF921bLwFsyaMWOGxo0bx5yLtsY0PfMg/E3h87bl5PiffBnoJOD6/QJdneSvX1GR75yN+ixLKi319LNLqJ9TCn28sficTSBgAG0ItSxgi3AuZBkZnkmZ9Ta+q2MYksvl6XeycC7Y4YSTUIX6OYMZR/1+sficTSBgAG0ItSxgi3AuZA6HZ8WH1PDi632dm9twxUM4F+xwwkmoQv2cwYyjfr9YfM4mEDCANoRaFkGKp3oLUvTGG+6FLDPTs0SzTx/fdqez8aWb4VywwwknXqH83YbyOcMZrx2f004hz/SIU0zyRFt2/Phxy+l0+p3kqRMTPV0uF5M2LSv8pX7BLt8MVyyWYPqb5BnMZMJQ/o78fU6XK7Clm94JqMGurojF70Ko4w3ncwaAVSRNIGCgtQl2RQe1LAIQT/UW7BivZQV/EYzwhczWsZ485mDDSbSXt4Y73nCOCwABowkEDLQmodazaHO1LIK5IMVbvYWWVtDJpgtZxETzdyHa47XjuGbEXcBYsWKF1bdvXysxMdEaNWqU9e677wZ03Jo1ayxJ1pQpUwI+FwEDrUW49SzaTC2LYC+e8VZvIVYFnU7+zNF8FBRN4f7dtkJxFTDWrl1rdejQwXr++eet//3f/7Vuvvlm69RTT7X27dvX5HElJSVWnz59rIyMDAIG2hzvXAp/8yiYS3GSUC6e4RRIisUFKRYFndqKcP5uW6m4KrT1xBNP6Oabb9YNN9ygs88+W08//bSSkpL0/PPPN3qMaZqaNWuWli5dqv79+0dxtEDLQD2LAIRaDCre6i3EoqBTW9HCln3Gm5gGjJqaGn3wwQeaMGFCXVtCQoImTJigbdu2NXrcAw88oF69eummm25q9hzV1dWqqqry+QLiHfUsAhDqxTPW9RaCXQ4Zi4JObUVLW/YZZ2IaMA4ePCjTNJWSkuLTnpKSooqKCr/HvPnmm3ruuef07LPPBnSOZcuWKTk5ue7L5XKFPW4g1qhnEYBQL56xrLfgdkvp6dL48dLMmZ7v6eme9sbEoqBTWxHO3y3iq9DWoUOHdN111+nZZ59Vjx49Ajpm4cKFqqysrPsqLS2N8CiByMvIyJDT6ZTRyIXMMAy5XC5ltOV/WYVz8Qy1QFI4FyS3W8rKanjXpazM095UyIh2Qae2JNS/W8iwLH8PKKOjpqZGSUlJys/P19SpU+va58yZo2+//VYvvfSST//i4mINGzbMZ2Ol2tpaSZ5HK3v27NGAAQOaPGdVVZWSk5NVWVmprl272vdhgChzu93KyspSgmXpQklpksolvSmp1jCUn5+vzKb+z880PY8Hyss9F9mMjNb1LzHT9Pzrv6zM/zwMw/BcJEpKGv/cof4dud2e+R8nhwWXyxMu/P038Y61sUc6gYw11PF6g43k+/fkDR1cRD1a+/9eAhTUNTTSM06bM2rUKOvWW2+te22aptWnTx9r2bJlDfp+99131q5du3y+pkyZYl1yySXWrl27rOrq6mbPxyoStCbbfv5zq8zh8JnRXuZwWNt+/vOmD4x2IahYiZdiULFeDhmP9SwQE8FcQ9tFI/E0Zf78+ZozZ45GjBihUaNGKTc3V0eOHNENN9wgSZo9e7b69OmjZcuWqWPHjjrnnHN8jj/11FMlqUE7EE9M01RRUZHKy8uVlpamjIyM5rdAd7t1/uOPy6r3r/O02lr1fvxx6fzz/f/L0/sv1vr/qvfeim9N/2L13t6ufzfB6Wz8boJdHA5p3LjA+sZ6smVmpjRlCv9Ch61iHjCmT5+uAwcO6L777lNFRYWGDh2qTZs21U383Lt3rxIS4mqqCBAUt9ut7Oxsn2WnTqdTeXl5jT/iOGkJZv2n54ZleW5v5+R4LhonXySaW7rZ2HF2Cec2c6jHxsPFsyVMtgwmEAGBiPwNlZaFRyRoSUKuxhnqLXW7bsXbtUlVoI9lWvsjHbs2DwMiLK4KbQFtlWmays7ObvCIQ1JdW05Ojkx/dRBCvaVux634UJZShrNCIpxj4wXLIdEKETCAGAmrGmeot9TDvRUfysU+1Iqa4R4bb1gOiVaGgAHESFjVOEOtXxBO3YNQL/bhlKNua6WsMzOlL7+UCgqk1as930tKCBeISwQMIEbCqsYZ6i31cG7Fh3qxD+exTKxXV8SCd7LljBme7zwWQZwiYAA2Mk1ThYWFWrNmjQoLC/3Pnzgh7Gqcod5SD/W4UC/24TyWaQmrKwCEJKaVPGOBSp6IlFCWm3qrcUrymezpDR3NVuOUQl++GexxhYWeCZ3NKSjwXe4YTkVNO6pxArBNXFXyjDaWqSISvMtNEyTrYsm69sR3x4klp40uNz1xrNPp9Fmm6nK5mjwmJsJZShlORc1YVuME4COYayh3MIAwmaap9PR0jfzqK+VJOnm/3lJJOZK2u1wqKSlptDpnSJU8YyGcfSuC3Z/DrmMB2CaYaygBAwhTYWGhlo8fr/wTr0+e2FR74nuWpNsLCjSuNVRKDOdiH4tKngBsE8w1NOalwoF4V1FWphPrMhrMmk6QJ2TkSnq7rCyaw4qccEpvh1OOmlLWQFwhYABhOuvAAZ/HIvUlSDpd0jcHDkRpRFHAxR5AM1imCoTp3J49be0HAK0BAQMIU0L9ehJh9gOA1oBHJEB9wU4mPFF+2/rqqwZbp0uedadGY+W3AaCV4g4GcLJQdgo9UX7bMAxZ9apyWobhKZrFTpgA2hgCBuB1osaDVW+/DSuQbcFPlN826j0GMdgJE0AbRR0MQKorSd3sY47mSlJTqwFAK0YdDCBYJ3YKbWQTc0+7d6fQppZnsnwTACTxiASQJNUGWAQr0H4A0NYRMABJHwVYBCvQfgDQ1hEwAEm7e/ZUqf61d0h9tZL2nugHAGgeAQOQlNqnj7JP/Ll+yPC+zjnRDwDQPAIGICkjI0PbnU79u6T6syy+kvTvkt53uZQRqWJZpikVFkpr1ni+m2ZkzgMAUULAACQ5HA7l5eVpo2Gon6Rxkmac+N5f0kbDUG5urhyRWHIaSnEvAGjhCBjACZmZmcrPz1ea06k3JK2V9Iak3i6X8vPzlRmJYlkninupXnEvBVLcCwBaMAptAfWYpqmioiKVl5crLS1NGRkZkblzcaK4V4Nw4WUYktPZfHEvAIgSCm0BYXA4HBoXjWJZJ4p7NcqyAivuBQAtEAEDrVLU7kKEo7zc3n4A0IIQMNDquN1u3XH77epXVqY0SeWSSvr00a+XL4/MPIpQpaXZ2w8AWhACBloVt9utP02bpjcluU5qLy0rU860adKGDS0nZGRkeOZYlJV5HofU552DEamlsQAQQawiQathmqZemztX6yXVL4fVR9J6SZvmzpXZUmpMOBxSXp7nz0a9bda8r3NzmeAJIC4RMNBqFBUW6r5//ENSw19s7+t7//EPFRUWRnNYTcvMlPLzpfoVQp1OT3tLudsCAEHiEQlaDbOw0OexSH0Jkk6X9PfCQunSS6MzqEBkZkpTpnhWi5SXe+ZcZGRw5wJAXCNgoNUIdCpki5wy6XCwFBVAq8IjErQaZwZ4gQ60HwAgdNzBQItm1tRo129/q6Off66kAQM0+JZb5OjQwW9fx7hxOtq9uzr+4x9+k3OtpO+7d1cSAQMAIo47GGix3rnrLu1LStLQO+7Q2BUrNPSOO7QvKUnv3HWX/wMcDiU984wM+d9y3ZCU9MwzzG0AgCggYCDyQtiK/J277tKoxx5Tar2+qaapUY891njIyMyUsWGDDKfTp9lwOmVs2MCqDACIEjY7Q2S53VJ2tu+eG06np/5DIxd7s6ZG+5KSlGqajT7qKHc4lHr0aKOPS2SarMoAAJsFcw3lDgYiJ8StyHf99rfq3Ui4kDy/tH1MU7t++9vGz+1dlTFjhuc74QIAooqAgcgwTc+dC383yLxtOTl+H5cc/fzzgE4RaD8AQPQRMBAZwWxFXk/SgAEBnSLQfgCA6CNgIDLC2Ip88C236GuHo8FKEK9aSWUOhwbfckvIwwMARBYBA5ERxlbkjg4dtHf+fEn+l5tKUun8+Y1P8AQAxBwBA5Hh3Yq8/i6hXoYhuVyNbkV+/qOP6r2f/1wV9SZnljsceu/nP9f5jz5q94gBADZimSoix7uKRPKd7OkNHQHsFhpMJU8AQGQFcw0lYCCy/NXBcLmk3FyKXgFAnAnmGspeJIgstiIHgDaJgIGIMyUVSSqXZ6v0DEnECwBo3QgYCFwI5bfdbreys7P11UmPSJxOp/Ly8pTJIxIAaLVYRYLAuN1Sero0frw0c6bne3p6o+W+PYe4lZWV5RMuJKmsrExZWVlyN3EsACC+MckTzfOuBqn/q9LEahDTNJWent4gXPzrUENOp1MlJSVyMB8DAOICm53BPiHuKVJUVNRouPAcaqm0tFRFfkqFAwDiHwEDTQtxT5HyAEuFB9oPABBfCBhoWoh7iqQFWCo80H4AgPhCwEDTQtxTJCMjQ06nU0YjpcINw5DL5VJGI6XCAQDxjYCBpoW4p4jD4VBeXt6JLka9Qzyvc3NzmeAJAK0UAQNNczikE0GhQcjwvs7N9VsPIzMzU/n5+erTp49Pu9PpVH5+PnUwAKAVY5kqAhPGniKmaaqoqEjl5eVKS0tTRkYGdy4AIA6x2VkTCBhhCKGSJwCg9WCzM0SGwyGNGxfrUQAA4gBzMAAAgO0IGAAAwHY8IkHAmKwJAAgUAQMBYdt1AEAweESCZrHtOgAgWCxTbWuCXGrKtusAAC+2a4d/breUni6NHy/NnOn5np7uaW8E264DAEJBwGgr3G4pK6vh1utlZZ72RkIG264DAEJBwGgLTNNT5tvf0zBvW06Op189bLsOAAgFAaMtKCpqeOfiZJYllZZ6+tXDtusAgFAQMNqCQB9f+OnHtusAgFAQMNqCQB9fNNKPbdcBAMFimWpbYJqe1SJlZf7nYRiG5HRKJSXNLlmlkicAtF3spgpfDoeUl+dZLWIYviHD+9gjN7fZrdcdDofGsZsqACAAPCJpKzIzpfx8qd5jDjmdnnYecwAAbMQdjLYkM1OaMiWoSp4AAISCgNHWOBwSjzkAABFGwGhjmKgJAIgGAkYbwpbrAIBoYZJnG8GW6wCAaCJgtAGmaSo7O1v+Sp5423JycmT62YsEAIBQtIiA8eSTTyo9PV0dO3bU6NGj9d577zXa99lnn1VGRoa6deumbt26acKECU32B1uuAwCiL+YBY926dZo/f76WLFmiHTt2aMiQIZo4caL279/vt39hYaFmzJihgoICbdu2TS6XS5dffrnKysqiPPL4wZbrAIBoi3mp8NGjR2vkyJFasWKFJKm2tlYul0u33Xab7r777maPN01T3bp104oVKzR79uwGP6+urlZ1dXXd66qqKrlcrjZVKrywsFDjx49vtl9BQQGVOgEAjQqmVHhM72DU1NTogw8+0IQJE+raEhISNGHCBG3bti2g9zh69KiOHTum0047ze/Ply1bpuTk5Lovl8tly9jjCVuuAwCiLaYB4+DBgzJNUykpKT7tKSkpqqioCOg9FixYoN69e/uElJMtXLhQlZWVdV+lpaVhj7tFME2psFBas8bzvYkJmmy5DgCItpjPwQjHL3/5S61du1YbN25Ux44d/fZJTExU165dfb7intvt2R11/Hhp5kzP9/R0T3sj2HIdABBNMS201aNHDzkcDu3bt8+nfd++fUpNTW3y2Mcff1y//OUv9frrr+vcc8+N5DBbFrfbsytq/akzZWWe9iY2LsvMzNSUKVOo5AkAiLiY3sHo0KGDhg8fri1bttS11dbWasuWLRozZkyjxz366KN68MEHtWnTJo0YMSIaQ20ZTFPKzm4YLqR/teXkNPu4ZNy4cZoxY4bGjRtHuAAARETMH5HMnz9fzz77rH7/+9/r008/1X/8x3/oyJEjuuGGGyRJs2fP1sKFC+v6P/LII1q8eLGef/55paenq6KiQhUVFTp8+HCsPkL0FBVJTdSzkGVJpaWefgAAxFDM9yKZPn26Dhw4oPvuu08VFRUaOnSoNm3aVDfxc+/evUpI+FcOeuqpp1RTU6OsrCyf91myZInuv//+aA49+gKtU0E9CwBAjMW8Dka0BbOGt8UpLPRM6GxOQQFbsgMAbBc3dTAQpIwMyemUGqlnIcOQXC5PPwAAYoiAEU8cDulEPYsGIcP7OjfX0w8AgBgiYMSbzEzPUtR69SzkdDa5RBUAgGiK+SRPhCAzU5oyxbNapLxcSkvzPBbhzgUAoIUgYMQrh4OJnACAFotHJAAAwHYEDAAAYDsCBgAAsB1zMOKUaZpsWgYAaLEIGHHI7XYrOztbX520L4nT6VReXh7brgMAWgQekcQZt9utrKwsn3AhSWVlZcrKypLb7Y7RyAAA+BcCRhwxTVPZ2dnyt32Mty0nJ0dmE9u1AwAQDQSMOFJUVNTgzsXJLMtSaWmpitiuHQAQYwSMOFIe4DbsgfYDACBSCBhxJC0tzdZ+AABECgEjjmRkZMjpdMpoZLt2wzDkcrmUwXbtAIAYI2DEEYfDobwT27XXDxne17m5udTDAADEHAEjzmRmZio/P1996m3X7nQ6lZ+fTx0MAECLYFj+1jy2YlVVVUpOTlZlZaW6du0a6+GEjEqeAIBoC+YaSiXPWDJNqahIKi+X0tKkjAzPNuwBcDgcGsd27QCAFoqAEStut5SdLZ1c18LplPLyJB5zAADiHHMwYsHtlrKyfMOFJJWVedop9w0AiHMEjGgzTc+dC39TX7xtOTmefgAAxCkCRrQVFTW8c3Eyy5JKSz39AACIUwSMaAu0jDflvgEAcYyAEW2BlvGm3DcAII4RMKItI8OzWqSRct8yDMnl8vQDACBOETCizeHwLEWVGoYM7+vc3IDrYQAA0BIRMGIhM1PKz5fqlfuW0+lppw4GACDOUWgrVjIzpSlTQq7kCQBAS0bAiCWHQ6LcNwCgFeIRCQAAsB0BAwAA2I6AAQAAbEfAAAAAtmOSZwyZpqmioiKVl5crLS1NGRkZcrCKBADQChAwYsTtdis7O1tfnbTxmdPpVF5enjKpgwEAiHM8IokBt9utrKwsn3AhSWVlZcrKypLb7Y7RyAAAsAcBI8pM01R2drYsy2rwM29bTk6OTNOM9tAAALANASPKioqKGty5OJllWSotLVVRUVEURwUAgL0IGFFWXl5uaz8AAFoiAkaUpaWl2doPAICWiIARZRkZGXI6nTLqb9V+gmEYcrlcysjIiPLIAACwDwEjyhwOh/Ly8iSpQcjwvs7NzaUeBgAgrhEwYiAzM1P5+fnq06ePT7vT6VR+fj51MAAAcc+w/K2XbMWqqqqUnJysyspKde3aNaZjoZInACCeBHMNpZJnDDkcDo0bNy7WwwAAwHY8IgEAALYjYAAAANsRMAAAgO0IGAAAwHYEDAAAYDsCBgAAsB0BAwAA2I46GOEyTamoSCovl9LSpIwMiWJZAIA2joARDrdbys6WvvrqX21Op5SXJ1HuGwDQhvGIJFRut5SV5RsuJKmszNPudsdmXAAAtAAEjFCYpufOhb9tXLxtOTmefgAAtEEEjFAUFTW8c3Eyy5JKSz39AABogwgYoSgvt7cfAACtDAEjFGlp9vYDAKCVIWCEIiPDs1rEMPz/3DAkl8vTDwCANoiAEQqHw7MUVWoYMryvc3OphwEAaLMIGKHKzJTy86U+fXzbnU5PO3UwAABtGIW2wpGZKU2ZQiVPAADqIWCEy+GQxo2L9SgAAGhRCBhhMk1TRUVFKi8vV1pamjIyMuTgDgYAoI0jYITB7XYrOztbX51UdMvpdCovL0+ZzMEAALRhTPIMkdvtVlZWlk+4kKSysjJlZWXJzV4kAIA2jIARAtM0lZ2dLcvPXiTetpycHJnsRQIAaKMIGCEoKipqcOfiZJZlqbS0VEXsRQIAaKMIGCEoD3CPkUD7AQDQ2hAwQpAW4B4jgfYDAKC1IWCEICMjQ06nU0Yje5EYhiGXy6UM9iIBALRRBIwQOBwO5Z3Yi6R+yPC+zs3NpR4GAKDNImCEKDMzU/n5+epTby8Sp9Op/Px86mAAANo0w/K31rIVq6qqUnJysiorK9W1a9ew349KngCAtiKYayiVPMPkcDg0jr1IAADwwSMSAABgOwIGAACwHQEDAADYrkUEjCeffFLp6enq2LGjRo8erffee6/J/uvXr9dZZ52ljh07avDgwXr11VejNFIAABCImAeMdevWaf78+VqyZIl27NihIUOGaOLEidq/f7/f/m+//bZmzJihm266SR9++KGmTp2qqVOn6uOPP47yyAEAQGNivkx19OjRGjlypFasWCFJqq2tlcvl0m233aa77767Qf/p06fryJEj+vOf/1zXdv7552vo0KF6+umnmz2f3ctUAQBoK+JmmWpNTY0++OADLVy4sK4tISFBEyZM0LZt2/wes23bNs2fP9+nbeLEiXrxxRf99q+urlZ1dXXd68rKSkmevyQAABA477UzkHsTMQ0YBw8elGmaSklJ8WlPSUnR7t27/R5TUVHht39FRYXf/suWLdPSpUsbtLtcrhBHDQBA23bo0CElJyc32afVF9pauHChzx2P2tpaffPNN+revXujm5UFq6qqSi6XS6WlpVF97BKL83LO1nVOAAiGZVk6dOiQevfu3WzfmAaMHj16yOFwaN++fT7t+/btU2pqqt9jUlNTg+qfmJioxMREn7ZTTz019EE3oWvXrjG5MMTivJyzdZ0TAALV3J0Lr5iuIunQoYOGDx+uLVu21LXV1tZqy5YtGjNmjN9jxowZ49NfkjZv3txofwAAEH0xf0Qyf/58zZkzRyNGjNCoUaOUm5urI0eO6IYbbpAkzZ49W3369NGyZcskSdnZ2br44ov1q1/9SldddZXWrl2r999/X88880wsPwYAADhJzAPG9OnTdeDAAd13332qqKjQ0KFDtWnTprqJnHv37lVCwr9utIwdO1arV6/Wvffeq3vuuUcDBw7Uiy++qHPOOSdWH0GJiYlasmRJg0cxrfG8nLN1nRMAIiXmdTAAAEDrE/NKngAAoPUhYAAAANsRMAAAgO0IGAAAwHYEDBsEu918OJYtW6aRI0eqS5cu6tWrl6ZOnao9e/ZE7Hz+/PKXv5RhGMrJyYnoecrKyvTjH/9Y3bt3V6dOnTR48GC9//77ET2naZpavHix+vXrp06dOmnAgAF68MEHA6q7H6itW7dq8uTJ6t27twzDaLCPjmVZuu+++5SWlqZOnTppwoQJ+vvf/27b+QEgGggYYQp2u/lwvfHGG5o3b57eeecdbd68WceOHdPll1+uI0eOROR89W3fvl3/9V//pXPPPTei5/nnP/+pCy64QO3bt9drr72mTz75RL/61a/UrVu3iJ73kUce0VNPPaUVK1bo008/1SOPPKJHH31Uv/nNb2w7x5EjRzRkyBA9+eSTfn/+6KOPavny5Xr66af17rvvqnPnzpo4caK+//5728YAABFnISyjRo2y5s2bV/faNE2rd+/e1rJly6Jy/v3791uSrDfeeCPi5zp06JA1cOBAa/PmzdbFF19sZWdnR+xcCxYssC688MKIvX9jrrrqKuvGG2/0acvMzLRmzZoVkfNJsjZu3Fj3ura21kpNTbUee+yxurZvv/3WSkxMtNasWRORMQBAJHAHIwze7eYnTJhQ19bcdvN2824/f9ppp0X8XPPmzdNVV13l83kj5eWXX9aIESP07//+7+rVq5eGDRumZ599NuLnHTt2rLZs2aK//e1vkqSdO3fqzTff1JVXXhnxc0tSSUmJKioqfP6Ok5OTNXr06Kj9TgGAHWJeyTOehbLdvJ1qa2uVk5OjCy64IOKVTNeuXasdO3Zo+/btET2P1xdffKGnnnpK8+fP1z333KPt27fr9ttvV4cOHTRnzpyInffuu+9WVVWVzjrrLDkcDpmmqYceekizZs2K2DlPVlFRIUl+f6e8PwOAeEDAiGPz5s3Txx9/rDfffDOi5yktLVV2drY2b96sjh07RvRcXrW1tRoxYoQefvhhSdKwYcP08ccf6+mnn45owHjhhRf0pz/9SatXr9YPf/hDFRcXKycnR717947oeQGgteERSRhC2W7eLrfeeqv+/Oc/q6CgQE6nM6Ln+uCDD7R//36dd955ateundq1a6c33nhDy5cvV7t27WSapu3nTEtL09lnn+3TNmjQIO3du9f2c53s5z//ue6++25de+21Gjx4sK677jrdcccddZvtRZr39yYWv1MAYCcCRhhC2W4+XJZl6dZbb9XGjRv117/+Vf369YvIeU526aWXateuXSouLq77GjFihGbNmqXi4mI5HA7bz3nBBRc0WH77t7/9TX379rX9XCc7evSoz+Z6kuRwOFRbWxvR83r169dPqampPr9TVVVVevfddyP2OwUAkcAjkjA1t9283ebNm6fVq1frpZdeUpcuXeqeyycnJ6tTp04ROWeXLl0azPHo3LmzunfvHrG5H3fccYfGjh2rhx9+WNdcc43ee+89PfPMM3rmmWcicj6vyZMn66GHHtLpp5+uH/7wh/rwww/1xBNP6MYbb7TtHIcPH9Znn31W97qkpETFxcU67bTTdPrppysnJ0e/+MUvNHDgQPXr10+LFy9W7969NXXqVNvGAAARF+tlLK3Bb37zG+v000+3OnToYI0aNcp65513InYuSX6/Vq5cGbFz+hPpZaqWZVn/8z//Y51zzjlWYmKiddZZZ1nPPPNMRM9nWZZVVVVlZWdnW6effrrVsWNHq3///taiRYus6upq285RUFDg97/hnDlzLMvyLFVdvHixlZKSYiUmJlqXXnqptWfPHtvODwDRwHbtAADAdszBAAAAtiNgAAAA2xEwAACA7QgYAADAdgQMAABgOwIGAACwHQEDAADYjoABAABsR8AA0CoYhqEXX3wx1sMAcAIBA0DYrr/+ehmG0eDriiuuiPXQAMQIm50BsMUVV1yhlStX+rQlJibGaDQAYo07GABskZiYqNTUVJ+vbt26SfI8vnjqqad05ZVXqlOnTurfv7/y8/N9jt+1a5cuueQSderUSd27d9fcuXN1+PBhnz7PP/+8fvjDHyoxMVFpaWm69dZbfX5+8OBBXX311UpKStLAgQP18ssvR/ZDA2gUAQNAVCxevFjTpk3Tzp07NWvWLF177bX69NNPJUlHjhzRxIkT1a1bN23fvl3r16/X66+/7hMgnnrqKc2bN09z587Vrl279PLLL+uMM87wOcfSpUt1zTXX6KOPPtKkSZM0a9YsffPNN1H9nABOiPV2rgDi35w5cyyHw2F17tzZ5+uhhx6yLMuyJFk/+9nPfI4ZPXq09R//8R+WZVnWM888Y3Xr1s06fPhw3c9feeUVKyEhwaqoqLAsy7J69+5tLVq0qNExSLLuvffeuteHDx+2JFmvvfaabZ8TQOCYgwHAFuPHj9dTTz3l03baaafV/XnMmDE+PxszZoyKi4slSZ9++qmGDBmizp071/38ggsuUG1trfbs2SPDMPT111/r0ksvbXIM5557bt2fO3furK5du2r//v2hfiQAYSBgALBF586dGzyysEunTp0C6te+fXuf14ZhqLa2NhJDAtAM5mAAiIp33nmnwetBgwZJkgYNGqSdO3fqyJEjdT9/6623lJCQoDPPPFNdunRRenq6tmzZEtUxAwgddzAA2KK6uloVFRU+be3atVOPHj0kSevXr9eIESN04YUX6k9/+pPee+89Pffcc5KkWbNmacmSJZozZ47uv/9+HThwQLfddpuuu+46paSkSJLuv/9+/exnP1OvXr105ZVX6tChQ3rrrbd02223RfeDAggIAQOALTZt2qS0tDSftjPPPFO7d++W5FnhsXbtWt1yyy1KS0vTmjVrdPbZZ0uSkpKS9Je//EXZ2dkaOXKkkpKSNG3aND3xxBN17zVnzhx9//33+vWvf60777xTPXr0UFZWVvQ+IICgGJZlWbEeBIDWzTA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" ] @@ -4323,7 +4357,7 @@ }, { "cell_type": "markdown", - "id": "9c48006a", + "id": "f3fe0cd4", "metadata": {}, "source": [ "Finally, we evaluate our model on our test data." @@ -4332,7 +4366,7 @@ { "cell_type": "code", "execution_count": 60, - "id": "e71eff9b", + "id": "9d632437", "metadata": { "lines_to_next_cell": 2 }, @@ -4340,7 +4374,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3e804034c1964ed38bbe2ca376491f54", + "model_id": "f8918dba5b82493399bab84a5d89568d", "version_major": 2, "version_minor": 0 }, @@ -4352,21 +4386,34 @@ "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_accuracy 0.40880000591278076\n", - " test_loss 2.4764862060546875\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - ] + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
+       "┃   Runningstage.testing    ┃                           ┃\n",
+       "┃          metric           ┃       DataLoader 0        ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
+       "│       test_accuracy       │    0.42969998717308044    │\n",
+       "│         test_loss         │    2.4235761165618896     │\n",
+       "└───────────────────────────┴───────────────────────────┘\n",
+       "
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To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n", - " warnings.warn(\n" - ] - }, { "data": { "text/plain": [ @@ -4979,7 +5018,7 @@ } ], "source": [ - "resize = Resize((232,232))\n", + "resize = Resize((232,232), antialias=True)\n", "crop = CenterCrop(224)\n", "normalize = Normalize([0.485,0.456,0.406],\n", " [0.229,0.224,0.225])\n", @@ -4992,7 +5031,7 @@ }, { "cell_type": "markdown", - "id": "a2c5aec2", + "id": "f6696ee2", "metadata": {}, "source": [ "We now set up the trained network with the weights we read in code block~6. The model has 50 layers, with a fair bit of complexity." @@ -5001,21 +5040,11 @@ { "cell_type": "code", "execution_count": 63, - "id": "7776ed1e", + "id": "2aabd724", "metadata": { "lines_to_next_cell": 0 }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -5201,7 +5230,7 @@ "Total params: 25,557,032\n", "Trainable params: 25,557,032\n", "Non-trainable params: 0\n", - "Total mult-adds (G): 24.54\n", + "Total mult-adds (Units.GIGABYTES): 24.54\n", "===================================================================================================================\n", "Input size (MB): 3.61\n", "Forward/backward pass size (MB): 1066.99\n", @@ -5226,7 +5255,7 @@ }, { "cell_type": "markdown", - "id": "0d29ab45", + "id": "c4ee6ebe", "metadata": {}, "source": [ "We set the mode to `eval()` to ensure that the model is ready to predict on new data." @@ -5235,7 +5264,7 @@ { "cell_type": "code", "execution_count": 64, - "id": "5c8e359d", + "id": "6d27342d", "metadata": { "lines_to_next_cell": 0 }, @@ -5432,7 +5461,7 @@ }, { "cell_type": "markdown", - "id": "228a6411", + "id": "3c1fbc71", "metadata": {}, "source": [ "Inspecting the output above, we see that when setting up the\n", @@ -5445,7 +5474,7 @@ { "cell_type": "code", "execution_count": 65, - "id": "80f19869", + "id": "efdbeda1", "metadata": {}, "outputs": [], "source": [ @@ -5454,7 +5483,7 @@ }, { "cell_type": "markdown", - "id": "e7bd653f", + "id": "38620865", "metadata": {}, "source": [ "Let’s look at the predicted probabilities for each of the top 3 choices. First we compute\n", @@ -5466,7 +5495,7 @@ { "cell_type": "code", "execution_count": 66, - "id": "6892597d", + "id": "82ceab1c", "metadata": {}, "outputs": [], "source": [ @@ -5476,7 +5505,7 @@ }, { "cell_type": "markdown", - "id": "b0f07763", + "id": "0e3ae755", "metadata": {}, "source": [ "In order to see the class labels, we must download the index file associated with `imagenet`. {This is avalable from the book website and [s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json](https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json).}" @@ -5485,7 +5514,7 @@ { "cell_type": "code", "execution_count": 67, - "id": "3eb1e1b0", + "id": "921ee168", "metadata": {}, "outputs": [], "source": [ @@ -5499,7 +5528,7 @@ }, { "cell_type": "markdown", - "id": "7779e914", + "id": "9fdd7587", "metadata": {}, "source": [ "We’ll now construct a data frame for each image file\n", @@ -5510,7 +5539,7 @@ { "cell_type": "code", "execution_count": 68, - "id": "0e89d251", + "id": "e7770017", "metadata": { "lines_to_next_cell": 2 }, @@ -5521,34 +5550,34 @@ "text": [ "Image: book_images/flamingo.jpg\n", " label prob\n", - "0 flamingo 0.591760\n", - "1 spoonbill 0.012386\n", - "2 American_egret 0.002105\n", + "0 flamingo 0.606624\n", + "1 spoonbill 0.013324\n", + "2 American_egret 0.002130\n", "Image: book_images/hawk.jpg\n", " label prob\n", - "0 great_grey_owl 0.287958\n", - "1 kite 0.039478\n", - "2 fountain 0.029384\n", + "0 kite 0.187797\n", + "1 robin 0.084580\n", + "2 great_grey_owl 0.059789\n", "Image: book_images/hawk_cropped.jpeg\n", - " label prob\n", - "0 kite 0.301841\n", - "1 jay 0.121659\n", - "2 magpie 0.015511\n", + " label prob\n", + "0 kite 0.454471\n", + "1 great_grey_owl 0.015789\n", + "2 jay 0.011916\n", "Image: book_images/huey.jpg\n", " label prob\n", - "0 Lhasa 0.151153\n", - "1 Shih-Tzu 0.129804\n", - "2 Tibetan_terrier 0.102400\n", + "0 Lhasa 0.260186\n", + "1 Shih-Tzu 0.097995\n", + "2 Tibetan_terrier 0.032107\n", "Image: book_images/kitty.jpg\n", - " label prob\n", - "0 tabby 0.173628\n", - "1 tiger_cat 0.110415\n", - "2 doormat 0.093447\n", + " label prob\n", + "0 Persian_cat 0.163612\n", + "1 tabby 0.074585\n", + "2 tiger_cat 0.042531\n", "Image: book_images/weaver.jpg\n", - " label prob\n", - "0 jacamar 0.287284\n", - "1 bee_eater 0.046768\n", - "2 bulbul 0.037507\n" + " label prob\n", + "0 jacamar 0.298104\n", + "1 macaw 0.068012\n", + "2 lorikeet 0.051065\n" ] } ], @@ -5563,7 +5592,7 @@ }, { "cell_type": "markdown", - "id": "7f9d3843", + "id": "12862208", "metadata": {}, "source": [ "We see that the model\n", @@ -5576,7 +5605,7 @@ { "cell_type": "code", "execution_count": 69, - "id": "69456669", + "id": "af2f9856", "metadata": { "lines_to_next_cell": 2 }, @@ -5593,7 +5622,7 @@ }, { "cell_type": "markdown", - "id": "64b33c4d", + "id": "d9e8d59c", "metadata": {}, "source": [ "## IMDB Document Classification\n", @@ -5620,7 +5649,7 @@ { "cell_type": "code", "execution_count": 70, - "id": "70b3ece2", + "id": "afd98123", "metadata": { "lines_to_next_cell": 0 }, @@ -5647,7 +5676,7 @@ }, { "cell_type": "markdown", - "id": "d6b73c18", + "id": "28a01855", "metadata": {}, "source": [ "The datasets `imdb_seq_train` and `imdb_seq_test` are\n", @@ -5665,7 +5694,7 @@ { "cell_type": "code", "execution_count": 71, - "id": "349b2af7", + "id": "5981eb05", "metadata": {}, "outputs": [ { @@ -5686,7 +5715,7 @@ }, { "cell_type": "markdown", - "id": "99d5a108", + "id": "b579cb29", "metadata": {}, "source": [ "For our first model, we have created a binary feature for each\n", @@ -5699,7 +5728,7 @@ { "cell_type": "code", "execution_count": 72, - "id": "ffa8da37", + "id": "f08024ba", "metadata": { "lines_to_next_cell": 0 }, @@ -5717,7 +5746,7 @@ }, { "cell_type": "markdown", - "id": "e53eea99", + "id": "c070a319", "metadata": {}, "source": [ "We’ll use a two-layer model for our first model." @@ -5726,7 +5755,7 @@ { "cell_type": "code", "execution_count": 73, - "id": "11eeeabb", + "id": "7fd34906", "metadata": { "lines_to_next_cell": 0 }, @@ -5754,7 +5783,7 @@ }, { "cell_type": "markdown", - "id": "943bf8d4", + "id": "fcc2a8af", "metadata": {}, "source": [ "We now instantiate our model and look at a summary." @@ -5763,19 +5792,9 @@ { "cell_type": "code", "execution_count": 74, - "id": "5fe55a29", + "id": "56f74fdb", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -5792,7 +5811,7 @@ "Total params: 160,353\n", "Trainable params: 160,353\n", "Non-trainable params: 0\n", - "Total mult-adds (G): 4.01\n", + "Total mult-adds (Units.GIGABYTES): 4.01\n", "===================================================================================================================\n", "Input size (MB): 1000.30\n", "Forward/backward pass size (MB): 6.60\n", @@ -5817,7 +5836,7 @@ }, { "cell_type": "markdown", - "id": "a49a0145", + "id": "a32aca43", "metadata": {}, "source": [ "We’ll again use\n", @@ -5835,7 +5854,7 @@ { "cell_type": "code", "execution_count": 75, - "id": "e1ebbc70", + "id": "3da7e0bc", "metadata": {}, "outputs": [], "source": [ @@ -5847,7 +5866,7 @@ }, { "cell_type": "markdown", - "id": "18076d4c", + "id": "940c8342", "metadata": {}, "source": [ "Having loaded the datasets into a data module\n", @@ -5858,19 +5877,17 @@ { "cell_type": "code", "execution_count": 76, - "id": "9feddeb2", + "id": "3b6de185", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:1789: UserWarning: MPS available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='mps', devices=1)`.\n", - " rank_zero_warn(\n", "\n", " | Name | Type | Params\n", "--------------------------------------------\n", @@ -5901,14 +5918,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:1892: 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/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", " rank_zero_warn(\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "44936d415c7e4ad6b38cd97c733a90be", + "model_id": "1b539194264149abbe1b411d90c66946", "version_major": 2, "version_minor": 0 }, @@ -6359,7 +6376,7 @@ }, { "cell_type": "markdown", - "id": "f28e6658", + "id": "5985c44a", "metadata": {}, "source": [ "Evaluating the test error yields roughly 86% accuracy." @@ -6368,7 +6385,7 @@ { "cell_type": "code", "execution_count": 77, - "id": "887d7dad", + "id": "97f86a32", "metadata": { "lines_to_next_cell": 2 }, @@ -6376,7 +6393,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "03f177eef9fe4ed090eef15f0a005581", + "model_id": "2e3673c6298342d79c32888a28e2c9cd", "version_major": 2, "version_minor": 0 }, @@ -6388,21 +6405,34 @@ "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_accuracy 0.8543599843978882\n", - " test_loss 1.1992340087890625\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - ] + "data": { + "text/html": [ + "
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+       "└───────────────────────────┴───────────────────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1m Runningstage.testing \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m┃\n", + "┃\u001b[1m \u001b[0m\u001b[1m metric \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m DataLoader 0 \u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n", + "│\u001b[36m \u001b[0m\u001b[36m test_accuracy \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 0.8492799997329712 \u001b[0m\u001b[35m \u001b[0m│\n", + "│\u001b[36m \u001b[0m\u001b[36m test_loss \u001b[0m\u001b[36m \u001b[0m│\u001b[35m \u001b[0m\u001b[35m 1.2849037647247314 \u001b[0m\u001b[35m \u001b[0m│\n", + "└───────────────────────────┴───────────────────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { "text/plain": [ - "[{'test_loss': 1.1992340087890625, 'test_accuracy': 0.8543599843978882}]" + "[{'test_loss': 1.2849037647247314, 'test_accuracy': 0.8492799997329712}]" ] }, "execution_count": 77, @@ -6417,7 +6447,7 @@ }, { "cell_type": "markdown", - "id": "d2f87545", + "id": "3d677b24", "metadata": {}, "source": [ "### Comparison to Lasso\n", @@ -6430,7 +6460,7 @@ { "cell_type": "code", "execution_count": 78, - "id": "055a9aeb", + "id": "e36e1542", "metadata": {}, "outputs": [], "source": [ @@ -6443,7 +6473,7 @@ }, { "cell_type": "markdown", - "id": "d8324d03", + "id": "8216f2e7", "metadata": {}, "source": [ "Similar to what we did in\n", @@ -6454,7 +6484,7 @@ { "cell_type": "code", "execution_count": 79, - "id": "e3e1e181", + "id": "ee6d6859", "metadata": { "lines_to_next_cell": 0 }, @@ -6467,7 +6497,7 @@ }, { "cell_type": "markdown", - "id": "73e7d53e", + "id": "cf9b703f", "metadata": {}, "source": [ "With `LogisticRegression()` the regularization parameter\n", @@ -6479,7 +6509,7 @@ { "cell_type": "code", "execution_count": 80, - "id": "dd64350c", + "id": "35a6e3c2", "metadata": { "lines_to_next_cell": 0 }, @@ -6494,7 +6524,7 @@ }, { "cell_type": "markdown", - "id": "f0e9739a", + "id": "49cec308", "metadata": {}, "source": [ "The path of 50 values takes approximately 40 seconds to run." @@ -6503,7 +6533,7 @@ { "cell_type": "code", "execution_count": 81, - "id": "0bf8b868", + "id": "a8943a6a", "metadata": {}, "outputs": [], "source": [ @@ -6519,7 +6549,7 @@ }, { "cell_type": "markdown", - "id": "95f4fbff", + "id": "4f20738d", "metadata": {}, "source": [ "The coefficient and intercepts have an extraneous dimension which can be removed\n", @@ -6529,7 +6559,7 @@ { "cell_type": "code", "execution_count": 82, - "id": "28256828", + "id": "08268ae5", "metadata": { "lines_to_next_cell": 0 }, @@ -6541,7 +6571,7 @@ }, { "cell_type": "markdown", - "id": "94e746f6", + "id": "94991ca8", "metadata": {}, "source": [ "We’ll now make a plot to compare our neural network results with the\n", @@ -6551,7 +6581,7 @@ { "cell_type": "code", "execution_count": 83, - "id": "a5945618", + "id": "e98f4506", "metadata": { "lines_to_next_cell": 0 }, @@ -6583,7 +6613,7 @@ }, { "cell_type": "markdown", - "id": "7dc7e494", + "id": "aac5c38c", "metadata": {}, "source": [ "Notice the use of `%%capture`, which suppresses the displaying of the partially completed figure. This is useful\n", @@ -6594,14 +6624,14 @@ { "cell_type": "code", "execution_count": 84, - "id": "74704884", + "id": "6925d53a", "metadata": { "lines_to_next_cell": 0 }, "outputs": [ { "data": { - "image/png": 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" ] @@ -6630,7 +6660,7 @@ }, { "cell_type": "markdown", - "id": "7898334d", + "id": "2a8b7736", "metadata": {}, "source": [ "From the graphs we see that the accuracy of the lasso logistic regression peaks at about $0.88$, as it does for the neural network.\n", @@ -6641,7 +6671,7 @@ { "cell_type": "code", "execution_count": 85, - "id": "b1ecfca8", + "id": "6d1f7885", "metadata": { "lines_to_next_cell": 2 }, @@ -6657,7 +6687,7 @@ }, { "cell_type": "markdown", - "id": "0169cd1b", + "id": "4f79c23a", "metadata": {}, "source": [ "## Recurrent Neural Networks\n", @@ -6667,7 +6697,7 @@ }, { "cell_type": "markdown", - "id": "6e7f96cc", + "id": "3d376496", "metadata": {}, "source": [ "### Sequential Models for Document Classification\n", @@ -6687,7 +6717,7 @@ { "cell_type": "code", "execution_count": 86, - "id": "5503cb3f", + "id": "b5c2b72c", "metadata": {}, "outputs": [], "source": [ @@ -6701,7 +6731,7 @@ }, { "cell_type": "markdown", - "id": "356b76f2", + "id": "4d1b3ef1", "metadata": {}, "source": [ "The first layer of the RNN is an embedding layer of size 32, which will be\n", @@ -6718,7 +6748,7 @@ }, { "cell_type": "markdown", - "id": "14ddd9a9", + "id": "fe55c7fa", "metadata": {}, "source": [ "The second layer is an LSTM with 32 units, and the output\n", @@ -6730,7 +6760,7 @@ { "cell_type": "code", "execution_count": 87, - "id": "8b683641", + "id": "8985cdb1", "metadata": { "lines_to_next_cell": 0 }, @@ -6751,7 +6781,7 @@ }, { "cell_type": "markdown", - "id": "b7903383", + "id": "78fc988d", "metadata": {}, "source": [ "We instantiate and take a look at the summary of the model, using the\n", @@ -6761,19 +6791,9 @@ { "cell_type": "code", "execution_count": 88, - "id": "702aa8de", + "id": "79184187", "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -6788,7 +6808,7 @@ "Total params: 328,577\n", "Trainable params: 328,577\n", "Non-trainable params: 0\n", - "Total mult-adds (M): 45.44\n", + "Total mult-adds (Units.MEGABYTES): 45.44\n", "===================================================================================================================\n", "Input size (MB): 50.00\n", "Forward/backward pass size (MB): 2.56\n", @@ -6813,7 +6833,7 @@ }, { "cell_type": "markdown", - "id": "f663b95c", + "id": "d5b2c85e", "metadata": {}, "source": [ "The 10,003 is suppressed in the summary, but we see it in the\n", @@ -6823,7 +6843,7 @@ { "cell_type": "code", "execution_count": 89, - "id": "e48aa272", + "id": "29036a47", "metadata": {}, "outputs": [], "source": [ @@ -6834,7 +6854,7 @@ { "cell_type": "code", "execution_count": 90, - "id": "143be7e8", + "id": "0a31576a", "metadata": { "lines_to_next_cell": 0 }, @@ -6843,12 +6863,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:1789: UserWarning: MPS available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='mps', devices=1)`.\n", - " rank_zero_warn(\n", "\n", " | Name | Type | Params\n", "--------------------------------------------\n", @@ -6878,7 +6896,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1ee0aabd8caf403c93b8c4ba0a1c2507", + "model_id": "903e15e146454c9c83ea87b85af4a97b", "version_major": 2, "version_minor": 0 }, @@ -7188,7 +7206,7 @@ }, { "cell_type": "markdown", - "id": "55dc2b66", + "id": "a20a2113", "metadata": {}, "source": [ "The rest is now similar to other networks we have fit. We\n", @@ -7198,13 +7216,13 @@ { "cell_type": "code", "execution_count": 91, - "id": "9272e2ba", + "id": "b2602a79", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "92a1cacbb1944d74b3f3c0670eb84b63", + "model_id": "6f9781f37c4d428da10cd12b67dac6fb", "version_major": 2, "version_minor": 0 }, @@ -7216,21 +7234,34 @@ "output_type": "display_data" }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_accuracy 0.8452399969100952\n", - " test_loss 0.7559056878089905\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - ] + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┓\n",
+       "┃   Runningstage.testing    ┃                           ┃\n",
+       "┃          metric           ┃       DataLoader 0        ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━┩\n",
+       "│       test_accuracy       │    0.8501600027084351     │\n",
+       "│         test_loss         │    0.8030509352684021     │\n",
+       "└───────────────────────────┴───────────────────────────┘\n",
+       "
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0.8030509352684021, 'test_accuracy': 0.8501600027084351}]" ] }, "execution_count": 91, @@ -7244,7 +7275,7 @@ }, { "cell_type": "markdown", - "id": "eee55195", + "id": "54857d49", "metadata": {}, "source": [ "We once again show the learning progress, followed by cleanup." @@ -7253,7 +7284,7 @@ { "cell_type": "code", "execution_count": 92, - "id": "5d9d387e", + "id": "32c3e3da", "metadata": { "lines_to_next_cell": 2 }, @@ -7270,7 +7301,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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t2LFDt956q0499VTdc889mjRpkj755BOtW7dOb731liQppoHfQ1VVlVJTUzVy5Eh99NFH2rdvn2655RbNnDnTJ2Tl5+crPj5e+fn52r17tyZNmqQhQ4bo1ltvPen7Qa26GUjT09PlcDh8BqgyAymAVmG1M+Xl5ZYkq7y8vN5jhw8ftj799FPr8OHD/1lYWWlZtfGh9W+VlU1+Xzt37rQkWfn5+d5lKSkp1g033NDg+r/4xS+s//f//p/3/iWXXGJlZGR47/fq1ct66qmnLMuyrDfffNPq0KGDVVxc7H3873//uyXJWrNmTaM1Pf7449bQoUO99+fPn28NHjy43nrHbue5556zunTpYlUe895ff/11KywszCotLbUsy7KmTZtm9erVyzp69Kh3nV/96lfWpEmTGq2lwc8WlmVZ1iuvvGK5XC5LkveWmJhovfLKK6ZLAxBkTnQMbQ5aQk4mKqq2RaIpNm6Uxo07+XpvvCH9/OdNe+0m6t+/vy666CK98MILGjVqlHbv3q2CggI9/PDDcrvdWrhwof72t7+puLhYNTU1qq6ubvKYj507dyoxMVE9e/b0Lhs5cmS99VatWqWnn35aX3zxhSorK3X06FG/Z9TbuXOnBg8erM7HtABdfPHF8ng82rVrl2JjYyVJ5557rs839Pj4eO3YscOv10KttLQ0TZgwgRlIAbQ6QsjJOBxN6hKRJF1xheRy1Q5CbWg8h8NR+/gVV0gB+AN/8803a9asWVqyZImWL1+uM888U5dccokeffRRLV68WFlZWRo4cKA6d+6szMxM1dTU2PbamzZt0vXXX68FCxYoNTVVMTExevnll/WHP/zBttc4VseOHX3uOxwOeTyegLxWe8AMpABMYGCqnZxO6aerfOr4wX5197OyAhJAJOnaa69VWFiYsrOz9ec//1m//vWv5XA49N5772nChAm64YYbNHjwYPXp00f//ve/m7zdAQMGqKioyOdUzQ8++MBnnffff1+9evXS/fffr2HDhqlv3776+uuvfdYJDw8/6cRXAwYM0Pbt21VVVeVd9t577yksLEz9+vVrcs0AgOBHCLFbWpqUkyMdd5VPuVy1ywN4lc9TTjlFkyZN0ty5c1VSUqKbbrpJktS3b1+tX79e77//vnbu3Knf/OY3Kisra/J2x4wZo7PPPlvTpk3T9u3bVVBQoPvvv99nnb59+2rPnj16+eWX9cUXX+jpp5/WmjVrfNZJSkpSYWGhtm3bpv3796u6urrea11//fXq1KmTpk2bpk8++UT5+fmaNWuWbrzxRm9XTHvmdru1YcMGrVy5Uhs2bGA2UwAhjRASCGlp0ldfSfn5UnZ27c/CwoAGkDo333yzvv/+e6WmpnrHcDzwwAO64IILlJqaqlGjRikuLk4TJ05s8jbDwsK0Zs0aHT58WCNGjNAtt9yi3//+9z7rXHXVVbrrrrs0c+ZMDRkyRO+//77mzZvns84111yjsWPHavTo0Tr99NMbPE04KipKb775pg4cOKDhw4crPT1dl112mZ555hn/fxltTG5urpKSkjR69GhNmTJFo0ePVlJSEtd3ARCyHJbVxMko2ogTXYaYy723XaH+2dZdaO743bXuVNqcnJwWX/EWAE7mRMfQ5qAlBAhyXGgOQFtFCAGCHBeaA9BWEUKAIMeF5gC0VcwTAgSA2+22bfIvLjQHoK2iJaQB7WysbrvQmp+p3WexcKE5AG0VIeQYdbNwHjp0yHAlsFvdZ3r8TKt2qzuL5fgxHMXFxUpPT29WEKm70JykekGEC80BCGWconuckpISHTx4UD169FBUVFSj3z4RGizL0qFDh7Rv3z6ddtppAe2ycLvdSkpKanQQqcPhkMvlUmFhYbMCQ25urjIyMny2n5iYqKysLE7PBdAq7D5FlxByHMuyVFpaqoMHD7Z+cQiY0047TXFxcQENlRs2bNDo0aNPul5+fn6zr9Ni51gTAPCX3SGEganHcTgcio+PV48ePXTkyBHT5cAGHTt2bJUDdWucxcKF5gC0JYSQRjidTr5hwi+cxQIA/mFgKmATzmIBAP8QQgCbcBYLAPiHEALYKC0tTTk5OUpISPBZ7nK5uMgcAByHs2OAAOAsFgBtEWfHACGAs1gA4OTojgEAAEYQQgAAgBF0x6DdYtwGAJhFCEG71NB1WFwulxYvXswZLADQSuiOQbsTiCvdAgD8RwhBu+J2u5WRkaGGzkyvW5aZmSm3293apQFAu0MIQbtSUFBQrwXkWJZlqaioSAUFBa1YFQC0T4QQtCutcaVbAEDTEELQrnClWwAIHoQQtCtc6RYAggchBO0KV7oFgOBBCEG7w5VuASA4cBVdtFvMmAoA/uEquoBNuNItAJhFdwwAADCCEAIAAIwghAAAACMYE4KgxwBSAGibCCEIarm5ucrIyPC53ovL5dLixYs5lRYAQhzdMQhaubm5Sk9Pr3fBueLiYqWnpys3N9dQZQAAOxBCEJTcbrcyMjLU0DQ2dcsyMzPldrtbuzQAgE0IIQhKBQUF9VpAjmVZloqKilRQUNCKVQEA7EQIQVAqKSmxdT0AQPAhhCAoxcfH27oeACD4EEIQlFJSUuRyuepd6baOw+FQYmKiUlJSWrkyAIBdCCEISk6nU4sXL5akekGk7n5WVhbzhQBACCOEwDZut1sbNmzQypUrtWHDhhafuZKWlqacnBwlJCT4LHe5XMrJyWGeEAAIccZDyJIlS5SUlKROnTopOTlZmzdvbnTdI0eO6OGHH9aZZ56pTp06afDgwVq3bl0rVovG5ObmKikpSaNHj9aUKVM0evRoJSUltXguj7S0NH311VfKz89Xdna28vPzVVhYSAABgDbAYTU0EUMrWbVqlaZOnaqlS5cqOTlZWVlZWr16tXbt2qUePXrUW3/OnDn6y1/+oueff179+/fXm2++qdmzZ+v999/X+eef36TXrKioUExMjMrLyxUdHW33W2qX6iYVO/6/Ul23Ca0WANA22H0MNRpCkpOTNXz4cD3zzDOSJI/Ho8TERM2aNUv33ntvvfV79uyp+++/XzNmzPAuu+aaaxQZGam//OUvTXpNQoi93G63kpKSGp3Tw+FwyOVyqbCwkPEbABDi7D6GGuuOqamp0ZYtWzRmzJj/FBMWpjFjxmjTpk0NPqe6ulqdOnXyWRYZGal333230deprq5WRUWFzw32YVIxAEBzGQsh+/fvl9vtVmxsrM/y2NhYlZaWNvic1NRUPfnkk/r888/l8Xi0fv165ebmnnDCqkWLFikmJsZ7S0xMtPV9tHdMKgYAaC7jA1P9sXjxYvXt21f9+/dXeHi4Zs6cqenTpyssrPG3MXfuXJWXl3tvRUVFrVhx28ekYgCA5jIWQrp37y6n06mysjKf5WVlZYqLi2vwOaeffrrWrl2rqqoqff311/rss890yimnqE+fPo2+TkREhKKjo31usA+TigEAmstYCAkPD9fQoUOVl5fnXebxeJSXl6eRI0ee8LmdOnVSQkKCjh49qldeeUUTJkwIdLloBJOKAQCay2h3zOzZs/X888/rxRdf1M6dO3XHHXeoqqpK06dPlyRNnTpVc+fO9a7/4YcfKjc3V19++aUKCgo0duxYeTwe3XPPPabeAsSkYgCA5ulg8sUnTZqkb7/9Vg8++KBKS0s1ZMgQrVu3zjtYdc+ePT7jPX788Uc98MAD+vLLL3XKKado3Lhxeumll3TaaacZegeok5aWpgkTJqigoEAlJSWKj49XSkoKLSAAgEYZnSfEBOYJAQCgedrMPCEAAKB9I4QAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwooPpAtD63G63CgoKVFJSovj4eKWkpMjpdJouC0BzuN1SQYFUUiLFx0spKRL7M0IEIaSdyc3NVUZGhvbu3etd5nK5tHjxYqWlpRmsDIDfcnOljAzpmP1ZLpe0eLHE/owQQHdMO5Kbm6v09HSfACJJxcXFSk9PV25urqHKAPgtN1dKT/cNIJJUXFy7nP0ZIcBhWZZluojWVFFRoZiYGJWXlys6Otp0Oa3G7XYrKSmpXgCp43A45HK5VFhYSNcMEOzcbikpqX4AqeNw1LaIFBbSNdMeBbCLzu5jKC0h7URBQUGjAUSSLMtSUVGRCgoKWrEqAM1SUNB4AJEky5KKimrXQ/uSm1sbUEePlqZMqf2ZlBS0LWOEkHaipKTE1vXaBLdb2rBBWrmy9qfbbboioGmaup+2p/0ZIdlFx8DUdiI+Pt7W9UIeA/oQypq6nwbj/szZPP9h5+/C7a79m9bQCAvLqu2iy8yUJkwIqt83LSHtREpKilwulxwOR4OPOxwOJSYmKiUlpZUrMyAEvy0APlJSakNzI/uzHA4pMbF2vWASYl0FAWX37yJEu+gIIe2E0+nU4sWLJaleEKm7n5WV1fYHpZ7s24JU+20hWLtm6EKCVPtN9qf9uV4QqbuflRVU33gJ/8cIxO8iRLvoCCHtSFpamnJycpSQkOCz3OVyKScnp33MExKi3xYk8S2ytYRK0EtLk3JypOP2Z7lctcuDaX8m/PtuKxC/i1DtorPamfLyckuSVV5ebroUY44ePWrl5+db2dnZVn5+vnX06FHTJbWe7GzLqt3VT3zLzjZdqa9XXrEsh6N+nQ5H7e2VV0xX2Da88opluVy+v2OXK7h/v0ePWlZ+fu3/2fz82vvBJj+/aftdfr7pSuuz+/9EoH4XR4/W1tXQ34m6vxWJiS3+/2H3MZSBqe2Q0+nUqFGjTJdhRih+WwjRAWchp66J/Pjfc10TebC1LtRxOqVg359DtKsgIP8nAvW7qOuiS0+v/ZtwbM3B2kUnumPQ3oTigL5Q7kIKFaHeXRDsWiP8292NFordJqHURfcTQgiCn51/XEJxQF+ofosMJQS9wAp0+A/EeKlA/Z8I9O8iLU366ispP1/Kzq79WVgYlAFEIoQg2AXij0uofVsIxS6kQLP7W29rBL1QGfAaCIEM/4E66ybQ3SZS4L4I1XXRTZ5c+zOYvlQdz5aRJSGEgakhJNCDMUNhQJ9ltc6As1D5XVhWYAaPBnrgZCgOeA2Ehn4PiYnN/z3U7RuNfV4t2TdM/J9oye+ildh9DCWEIDgF8o9LKKoLZMcHETsCWSgdIAMVTAMZ9DizyZedgTeQQYHw3yBCSAsRQkJEKJ/SFyiB+OYUSgfIQAfTQAQ9wnRgBfqU+0CG/xBl9zGUMSEITgzGrM/uAWehdkZIoAePBmKsEANeAyvQ46VCbfxYCGKeEAQnBmM2zM45Ifw5QAbDPBStEUzT0mrnW7HromKE6cCqO9OkuLjhMO1w1D7eklPu7f4/AR+EEASn1vjj0t6F2gGytYKpnUGPMB1YrTVBVyhMCBei6I5BcArF+TyOFQqnY4baATIUJ5oLxZpDDV0mIY0QguAVqn9cQuVCc6F2gAzFYBqKNYeiEJugC//hsKyG2rrbroqKCsXExKi8vFzR0dGmy0FTuN2h0x/b2LUm6g44wRae6uqVGm7KDrZ6pdqaMzJ8x7MkJtYezIOt1jqhWDPQALuPoYSQ9iiUDuqhxO2ubfFobLBn3TiWwsLg+n2H4gEyFP8Ph2LNwHEIIS3U7kNIQwccl6u2yThYDzihYsOG2q6Xk8nPD75BbhwgATSB3cdQzo5pT0L1UuWhItTONjkWo/9xPIIpWgEDU9uLUJuYKhSF2tkmQGNCZXA1Qh4hpL1g5sbAC7WzTYCGBOqqtEADCCHBzM65JkK5qyBUcDomQh0tpmhlhJBgZXdzKF0FrSNU5zYBJFpM0eoYmBqMAjGAlGnQWw/XmkCoosUUrYyWkGATqOZQugpaV93ZJpMn1/7k94pQQIspWhkhJNgEsjmUrgIAJ8LgarQyumOCTaCbQ+kqANCY1roqLfATQkiwaY3mUCamAtCYuhbThmZWDuap/BGSmLY92LjdOhQbq07ffddgX5lH0o/duimqrIxvIwAChxlT0QCmbW/j3JIyJP23agPHsUHE89PPTEnPSuLPAYIeB7LQRYspWgEDU4NMQUGB/r/vvlO6pOLjHtsrKV3S8999pwLO00ewY+pvACdBCAkyJT8NOF0jKUnSKEmTf/rZ+6flx64HBCWm/gbQBISQIBN/zIBTj6R3JL38009PI+sBQYWpvwE0ESEkyKSkpMjlcsnRyHn6DodDiYmJSuE8fQQrpv4G0ESEkCDjdDq1+KeZTY8PInX3s7Ky5GRwH4IVU38DaCJCSBBKS0tTTk6OEo6b2dTlciknJ0dpnKePYMbU3wCaiHlCgpjb7VZBQYFKSkoUHx+vlJQUWkAQ/Nzu2rNgTnaxxMJCTtcFQgzzhLQjTqdTozhPH6GGqb8BNBHdMQDsx8USATQBLSEAAoOLJQI4CUIIgMBh6m8AJ0B3DAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADDCeAhZsmSJkpKS1KlTJyUnJ2vz5s0nXD8rK0v9+vVTZGSkEhMTddddd+nHH39spWoBAIBdjIaQVatWafbs2Zo/f762bt2qwYMHKzU1Vfv27Wtw/ezsbN17772aP3++du7cqWXLlmnVqlW67777WrlyAADQUkZDyJNPPqlbb71V06dP1znnnKOlS5cqKipKL7zwQoPrv//++7r44os1ZcoUJSUl6YorrtDkyZNP2noCAACCj7EQUlNToy1btmjMmDH/KSYsTGPGjNGmTZsafM5FF12kLVu2eEPHl19+qTfeeEPjxo1r9HWqq6tVUVHhcwMAAOYZu4ru/v375Xa7FRsb67M8NjZWn332WYPPmTJlivbv36+f/exnsixLR48e1e23337C7phFixZpwYIFttYOAABazvjAVH9s2LBBCxcu1J/+9Cdt3bpVubm5ev311/XII480+py5c+eqvLzceysqKmrFigEAQGOMtYR0795dTqdTZWVlPsvLysoUFxfX4HPmzZunG2+8UbfccoskaeDAgaqqqtJtt92m+++/X2Fh9TNVRESEIiIi7H8DAACgRYy1hISHh2vo0KHKy8vzLvN4PMrLy9PIkSMbfM6hQ4fqBQ2n0ylJsiwrcMUCAADbGWsJkaTZs2dr2rRpGjZsmEaMGKGsrCxVVVVp+vTpkqSpU6cqISFBixYtkiSNHz9eTz75pM4//3wlJydr9+7dmjdvnsaPH+8NIwAAIDQYDSGTJk3St99+qwcffFClpaUaMmSI1q1b5x2sumfPHp+WjwceeEAOh0MPPPCAiouLdfrpp2v8+PH6/e9/b+otAACAZnJY7awfo6KiQjExMSovL1d0dLTpcgAACBl2H0ND6uwYAADQdhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBF+h5CkpCQ9/PDD2rNnTyDqAQAA7YTfISQzM1O5ubnq06ePLr/8cr388suqrq4ORG0AAKANa1YI2bZtmzZv3qwBAwZo1qxZio+P18yZM7V169ZA1AgAANqgFl9F98iRI/rTn/6kOXPm6MiRIxo4cKDuvPNOTZ8+XQ6Hw646bcNVdAEAaB67j6EdmvvEI0eOaM2aNVq+fLnWr1+vCy+8UDfffLP27t2r++67T2+99Zays7NbXCAAAGib/A4hW7du1fLly7Vy5UqFhYVp6tSpeuqpp9S/f3/vOldffbWGDx9ua6EAAKBt8TuEDB8+XJdffrmeffZZTZw4UR07dqy3Tu/evXXdddfZUiAAAGib/A4hX375pXr16nXCdTp37qzly5c3uygAAND2+X12zL59+/Thhx/WW/7hhx/q//7v/2wpCgAAtH1+h5AZM2aoqKio3vLi4mLNmDHDlqIAAEDb53cI+fTTT3XBBRfUW37++efr008/taUoAADQ9vkdQiIiIlRWVlZveUlJiTp0aPYZvwAAoJ3xO4RcccUVmjt3rsrLy73LDh48qPvuu0+XX365rcUBAIC2y++miyeeeEI///nP1atXL51//vmSpG3btik2NlYvvfSS7QUCAIC2ye8QkpCQoI8//lh//etftX37dkVGRmr69OmaPHlyg3OGAAAANKRZgzg6d+6s2267ze5aAABAO9LskaSffvqp9uzZo5qaGp/lV111VYuLAgAAbV+zZky9+uqrtWPHDjkcDtVdhLfuirlut9veCgEAQJvk99kxGRkZ6t27t/bt26eoqCj961//0saNGzVs2DBt2LAhACUCAIC2yO+WkE2bNuntt99W9+7dFRYWprCwMP3sZz/TokWLdOedd+qf//xnIOoEAABtjN8tIW63W6eeeqokqXv37vrmm28kSb169dKuXbvsrQ4AALRZfreEnHfeedq+fbt69+6t5ORkPfbYYwoPD9dzzz2nPn36BKJGAADQBvkdQh544AFVVVVJkh5++GH98pe/VEpKirp166ZVq1bZXiAAAGibHFbd6S0tcODAAXXp0sV7hkwwq6ioUExMjMrLyxUdHW26HAAAQobdx1C/xoQcOXJEHTp00CeffOKzvGvXriERQAAAQPDwK4R07NhRZ5xxBnOBAACAFvP77Jj7779f9913nw4cOBCIegAAQDvh98DUZ555Rrt371bPnj3Vq1cvde7c2efxrVu32lYcAABou/wOIRMnTgxAGQAAoL2x5eyYUMLZMQAANI/Rs2MAAADs4nd3TFhY2AlPx+XMGQAA0BR+h5A1a9b43D9y5Ij++c9/6sUXX9SCBQtsKwwAALRtto0Jyc7O1qpVq/Tqq6/asbmAYUwIAADNE7RjQi688ELl5eXZtTkAANDG2RJCDh8+rKeffloJCQl2bA4AALQDfo8JOf5CdZZl6YcfflBUVJT+8pe/2FocAABou/wOIU899ZRPCAkLC9Ppp5+u5ORkdenSxdbiAABA2+V3CLnpppsCUAYAAGhv/B4Tsnz5cq1evbre8tWrV+vFF1+0pSgAAND2+R1CFi1apO7du9db3qNHDy1cuNCWogAAQNvndwjZs2ePevfuXW95r169tGfPHluKAgAAbZ/fIaRHjx76+OOP6y3fvn27unXrZktRAACg7fM7hEyePFl33nmn8vPz5Xa75Xa79fbbbysjI0PXXXddIGoEAABtkN9nxzzyyCP66quvdNlll6lDh9qnezweTZ06lTEhAACgyZp97ZjPP/9c27ZtU2RkpAYOHKhevXrZXVtAcO0YAACax+5jqN8tIXX69u2rvn37trgAAADQPvk9JuSaa67Ro48+Wm/5Y489pl/96le2FAUAANo+v0PIxo0bNW7cuHrLr7zySm3cuNGWogAAQNvndwiprKxUeHh4veUdO3ZURUWFLUUBAIC2z+8QMnDgQK1atare8pdfflnnnHOOLUUBAIC2z++BqfPmzVNaWpq++OILXXrppZKkvLw8ZWdnKycnx/YCAQBA2+R3CBk/frzWrl2rhQsXKicnR5GRkRo8eLDefvttde3aNRA1AgCANqjZ84TUqaio0MqVK7Vs2TJt2bJFbrfbrtoCgnlCAABoHruPoX6PCamzceNGTZs2TT179tQf/vAHXXrppfrggw9aXBAAAGgf/OqOKS0t1YoVK7Rs2TJVVFTo2muvVXV1tdauXcugVAAA4Jcmt4SMHz9e/fr108cff6ysrCx98803+uMf/xjI2gAAQBvW5JaQv//977rzzjt1xx13MF07AABosSa3hLz77rv64YcfNHToUCUnJ+uZZ57R/v37A1kbAABow5ocQi688EI9//zzKikp0W9+8xu9/PLL6tmzpzwej9avX68ffvghkHUCAIA2pkWn6O7atUvLli3TSy+9pIMHD+ryyy/Xa6+9Zmd9tuMUXQAAmidoTtGVpH79+umxxx7T3r17tXLlyhYXAwAA2o8WT1YWamgJAQCgeYKqJQQAAKC5CCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjAiKELJkyRIlJSWpU6dOSk5O1ubNmxtdd9SoUXI4HPVuv/jFL1qxYgAA0FLGQ8iqVas0e/ZszZ8/X1u3btXgwYOVmpqqffv2Nbh+bm6uSkpKvLdPPvlETqdTv/rVr1q5cgAA0BLGQ8iTTz6pW2+9VdOnT9c555yjpUuXKioqSi+88EKD63ft2lVxcXHe2/r16xUVFUUIAQAgxBgNITU1NdqyZYvGjBnjXRYWFqYxY8Zo06ZNTdrGsmXLdN1116lz584NPl5dXa2KigqfGwAAMM9oCNm/f7/cbrdiY2N9lsfGxqq0tPSkz9+8ebM++eQT3XLLLY2us2jRIsXExHhviYmJLa4bAAC0nPHumJZYtmyZBg4cqBEjRjS6zty5c1VeXu69FRUVtWKFAACgMR1Mvnj37t3ldDpVVlbms7ysrExxcXEnfG5VVZVefvllPfzwwydcLyIiQhERES2uFQAA2MtoS0h4eLiGDh2qvLw87zKPx6O8vDyNHDnyhM9dvXq1qqurdcMNNwS6TAAAEABGW0Ikafbs2Zo2bZqGDRumESNGKCsrS1VVVZo+fbokaerUqUpISNCiRYt8nrds2TJNnDhR3bp1M1E2AABoIeMhZNKkSfr222/14IMPqrS0VEOGDNG6deu8g1X37NmjsDDfBptdu3bp3Xff1T/+8Q8TJQMAABs4LMuyTBfRmioqKhQTE6Py8nJFR0ebLgcAgJBh9zE0pM+OAQAAoYsQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMKKD6QJCndvtVkFBgUpKShQfH6+UlBQ5nU7TZQEAEPQIIS2Qm5urjIwM7d2717vM5XJp8eLFSktLM1gZAADBj+6YZsrNzVV6erpPAJGk4uJipaenKzc311BlAACEBkJIM7jdbmVkZMiyrHqP1S3LzMyU2+1u7dIAAAgZhJBmKCgoqNcCcizLslRUVKSCgoJWrAoAgNBCCGmGkpISW9cDAKA9IoQ0Q3x8vK3rAQDQHhFCmiElJUUul0sOh6PBxx0OhxITE5WSktLKlQEAEDoIIc3gdDq1ePFiSaoXROruZ2VlMV8IAAAnQAhpprS0NOXk5CghIcFnucvlUk5ODvOEAABwEg6rofNM27CKigrFxMSovLxc0dHRLd4eM6YCANoLu4+hzJjaQk6nU6NGjTJdBgAAIYfuGAAAYAQhBAAAGEEIAQAARhBCAACAEYQQAABgBCEEAAAYQQgBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhBCAACAER1MF4A2xO2WCgqkkhIpPl5KSZGcTtNVAQCCFCEE9sjNlTIypL17/7PM5ZIWL5bS0szVBQAIWnTHoOVyc6X0dN8AIknFxbXLc3PN1AUACGqEELSM213bAmJZ9R+rW5aZWbseAADHIISgZQoK6reAHMuypKKi2vUAADgGIQQtU1Ji73oAgHaDEIKWiY+3dz0AQLtBCEHLpKTUngXjcDT8uMMhJSbWrgcAwDEIIWgZp7P2NFypfhCpu5+VxXwhAIB6CCFoubQ0KSdHSkjwXe5y1S5nnhAAQAOYrAz2SEuTJkxgxlQAQJMRQmAfp1MaNcp0FQCAEEF3DAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwwngIWbJkiZKSktSpUyclJydr8+bNJ1z/4MGDmjFjhuLj4xUREaGzzz5bb7zxRitVCwAA7NLB5IuvWrVKs2fP1tKlS5WcnKysrCylpqZq165d6tGjR731a2pqdPnll6tHjx7KyclRQkKCvv76a5122mmtXzwAAGgRh2VZlqkXT05O1vDhw/XMM89IkjwejxITEzVr1izde++99dZfunSpHn/8cX322Wfq2LFjk16jurpa1dXV3vsVFRVKTExUeXm5oqOj7XkjAAC0AxUVFYqJibHtGGqsO6ampkZbtmzRmDFj/lNMWJjGjBmjTZs2Nfic1157TSNHjtSMGTMUGxur8847TwsXLpTb7W70dRYtWqSYmBjvLTEx0fb3AgAA/GcshOzfv19ut1uxsbE+y2NjY1VaWtrgc7788kvl5OTI7XbrjTfe0Lx58/SHP/xBv/vd7xp9nblz56q8vNx7KyoqsvV9AACA5jE6JsRfHo9HPXr00HPPPSen06mhQ4equLhYjz/+uObPn9/gcyIiIhQREdHKlQIAgJMxFkK6d+8up9OpsrIyn+VlZWWKi4tr8Dnx8fHq2LGjnE6nd9mAAQNUWlqqmpoahYeHB7RmAABgH2PdMeHh4Ro6dKjy8vK8yzwej/Ly8jRy5MgGn3PxxRdr9+7d8ng83mX//ve/FR8fTwABACDEGJ0nZPbs2Xr++ef14osvaufOnbrjjjtUVVWl6dOnS5KmTp2quXPnete/4447dODAAWVkZOjf//63Xn/9dS1cuFAzZsww9RYAAEAzGR0TMmnSJH377bd68MEHVVpaqiFDhmjdunXewap79uxRWNh/clJiYqLefPNN3XXXXRo0aJASEhKUkZGhOXPmmHoLAACgmYzOE2KC3ec4AwDQXrSZeUIAAED7RggBAABGEEIAAIARhBAAAGAEIQQAABhBCAEAAEYQQgAAgBGEEAAAYAQhBAAAGEEIAQAARhi9dkyb4HZLBQVSSYkUHy+lpEhOp+mqAAAIeoSQlsjNlTIypL17/7PM5ZIWL5bS0szVBQBACKA7prlyc6X0dN8AIknFxbXLc3PN1AUAQIgghDSH213bAtLQBYjrlmVm1q4HAAAaRAhpjoKC+i0gx7Isqaiodj0AANAgQkhzlJTYux4AAO0QIaQ54uPtXQ8AgHaIENIcKSm1Z8E4HA0/7nBIiYm16wEAgAYRQprD6aw9DVeqH0Tq7mdlMV8IAAAnQAhprrQ0KSdHSkjwXe5y1S5nnhAAAE6IycpaIi1NmjCBGVMBAGgGQkhLOZ3SqFGmqwAAIOTQHQMAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMAIQggAADCCEAIAAIwghAAAACMIIQAAwAhCCAAAMIIQAgAAjCCEAAAAIwghAADACEIIAAAwghACAACMIIQAAAAjCCEAAMCIoAghS5YsUVJSkjp16qTk5GRt3ry50XVXrFghh8Phc+vUqVMrVgsAAOxgPISsWrVKs2fP1vz587V161YNHjxYqamp2rdvX6PPiY6OVklJiff29ddft2LFAADADsZDyJNPPqlbb71V06dP1znnnKOlS5cqKipKL7zwQqPPcTgciouL895iY2NbsWIAAGCHDiZfvKamRlu2bNHcuXO9y8LCwjRmzBht2rSp0edVVlaqV69e8ng8uuCCC7Rw4UKde+65Da5bXV2t6upq7/3y8nJJUkVFhU3vAgCA9qHu2GlZli3bMxpC9u/fL7fbXa8lIzY2Vp999lmDz+nXr59eeOEFDRo0SOXl5XriiSd00UUX6V//+pdcLle99RctWqQFCxbUW56YmGjPmwAAoJ357rvvFBMT0+LtGA0hzTFy5EiNHDnSe/+iiy7SgAED9N///d965JFH6q0/d+5czZ4923vf4/HowIED6tatmxwOhy01VVRUKDExUUVFRYqOjrZlm2gdfHahi88udPHZha7y8nKdccYZ6tq1qy3bMxpCunfvLqfTqbKyMp/lZWVliouLa9I2OnbsqPPPP1+7d+9u8PGIiAhFRET4LDvttNOaVe/JREdHs0OFKD670MVnF7r47EJXWJg9Q0qNDkwNDw/X0KFDlZeX513m8XiUl5fn09pxIm63Wzt27FB8fHygygQAAAFgvDtm9uzZmjZtmoYNG6YRI0YoKytLVVVVmj59uiRp6tSpSkhI0KJFiyRJDz/8sC688EKdddZZOnjwoB5//HF9/fXXuuWWW0y+DQAA4CfjIWTSpEn69ttv9eCDD6q0tFRDhgzRunXrvINV9+zZ49Ps8/333+vWW29VaWmpunTpoqFDh+r999/XOeecY+otKCIiQvPnz6/X7YPgx2cXuvjsQhefXeiy+7NzWHadZwMAAOAH45OVAQCA9okQAgAAjCCEAAAAIwghAADACEKIDZYsWaKkpCR16tRJycnJ2rx5s+mScBIPPfSQHA6Hz61///6my0IDNm7cqPHjx6tnz55yOBxau3atz+OWZenBBx9UfHy8IiMjNWbMGH3++edmioWPk312N910U739cOzYsWaKhY9FixZp+PDhOvXUU9WjRw9NnDhRu3bt8lnnxx9/1IwZM9StWzedcsopuuaaa+pNPnoyhJAWWrVqlWbPnq358+dr69atGjx4sFJTU7Vv3z7TpeEkzj33XJWUlHh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" ] @@ -7294,7 +7325,7 @@ { "cell_type": "code", "execution_count": 93, - "id": "7c6d1072", + "id": "be5a979e", "metadata": { "lines_to_next_cell": 2 }, @@ -7310,7 +7341,7 @@ }, { "cell_type": "markdown", - "id": "7d179385", + "id": "240618c9", "metadata": {}, "source": [ "### Time Series Prediction\n", @@ -7322,7 +7353,7 @@ { "cell_type": "code", "execution_count": 94, - "id": "8e2d1d5c", + "id": "cf219016", "metadata": {}, "outputs": [], "source": [ @@ -7337,7 +7368,7 @@ }, { "cell_type": "markdown", - "id": "6ad4a748", + "id": "2ebf00d3", "metadata": {}, "source": [ "Next we set up the lagged versions of the data, dropping\n", @@ -7347,7 +7378,7 @@ { "cell_type": "code", "execution_count": 95, - "id": "6f6d0e12", + "id": "c0d6bb22", "metadata": {}, "outputs": [], "source": [ @@ -7362,7 +7393,7 @@ }, { "cell_type": "markdown", - "id": "91a924d2", + "id": "53d15ddf", "metadata": {}, "source": [ "Finally, we extract the response, training indicator, and drop the current day’s `DJ_return` and\n", @@ -7372,7 +7403,7 @@ { "cell_type": "code", "execution_count": 96, - "id": "d3c961ec", + "id": "9de511d5", "metadata": { "lines_to_next_cell": 2 }, @@ -7400,7 +7431,7 @@ }, { "cell_type": "markdown", - "id": "1c5f8d2f", + "id": "9c61eaa2", "metadata": {}, "source": [ "We first fit a simple linear model and compute the $R^2$ on the test data using\n", @@ -7410,7 +7441,7 @@ { "cell_type": "code", "execution_count": 97, - "id": "cb89da88", + "id": "89666a56", "metadata": {}, "outputs": [ { @@ -7432,7 +7463,7 @@ }, { "cell_type": "markdown", - "id": "b92425ab", + "id": "c3997039", "metadata": {}, "source": [ "We refit this model, including the factor variable `day_of_week`.\n", @@ -7443,7 +7474,7 @@ { "cell_type": "code", "execution_count": 98, - "id": "55d921d7", + "id": "23ebf124", "metadata": { "lines_to_next_cell": 0 }, @@ -7456,7 +7487,7 @@ }, { "cell_type": "markdown", - "id": "afab736a", + "id": "8df4e475", "metadata": {}, "source": [ " Note that we do not have\n", @@ -7467,7 +7498,7 @@ { "cell_type": "code", "execution_count": 99, - "id": "4e87eeb9", + "id": "4190a4dc", "metadata": { "lines_to_next_cell": 0 }, @@ -7490,7 +7521,7 @@ }, { "cell_type": "markdown", - "id": "43309e3b", + "id": "d98cc235", "metadata": {}, "source": [ "This model achieves an $R^2$ of about 46%." @@ -7498,7 +7529,7 @@ }, { "cell_type": "markdown", - "id": "93c61d80", + "id": "131bfc1c", "metadata": {}, "source": [ "To fit the RNN, we must reshape the data, as it will expect 5 lagged\n", @@ -7519,7 +7550,7 @@ { "cell_type": "code", "execution_count": 100, - "id": "3689b318", + "id": "a2b41f92", "metadata": { "lines_to_next_cell": 0 }, @@ -7550,7 +7581,7 @@ }, { "cell_type": "markdown", - "id": "9dbcf9f7", + "id": "7b301214", "metadata": {}, "source": [ "We now reshape the data." @@ -7559,7 +7590,7 @@ { "cell_type": "code", "execution_count": 101, - "id": "5633e521", + "id": "dde73c9e", "metadata": { "lines_to_next_cell": 0 }, @@ -7582,7 +7613,7 @@ }, { "cell_type": "markdown", - "id": "bd3ae3ff", + "id": "4fa6cd7a", "metadata": {}, "source": [ "By specifying the first size as -1, `numpy.reshape()` deduces its size based on the remaining arguments.\n", @@ -7597,7 +7628,7 @@ { "cell_type": "code", "execution_count": 102, - "id": "979a6066", + "id": "6f9d6357", "metadata": {}, "outputs": [], "source": [ @@ -7618,7 +7649,7 @@ }, { "cell_type": "markdown", - "id": "14671ab2", + "id": "a5d720e7", "metadata": {}, "source": [ "We fit the model in a similar fashion to previous networks. We\n", @@ -7628,13 +7659,14 @@ "early stopping, since then the test performance would be biased.\n", "\n", "We form the training dataset similar to\n", - "our `Hitters` example." + "our `Hitters` example.\n", + " " ] }, { "cell_type": "code", "execution_count": 103, - "id": "3528f4e7", + "id": "a21ca47e", "metadata": {}, "outputs": [], "source": [ @@ -7648,7 +7680,7 @@ }, { "cell_type": "markdown", - "id": "1a731099", + "id": "0d627892", "metadata": {}, "source": [ "Following our usual pattern, we inspect the summary." @@ -7657,21 +7689,11 @@ { "cell_type": "code", "execution_count": 104, - "id": "795c283e", + "id": "8fa26b87", "metadata": { "lines_to_next_cell": 0 }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torchinfo/torchinfo.py:477: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " action_fn=lambda data: sys.getsizeof(data.storage()),\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/torch/storage.py:665: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n", - " return super().__sizeof__() + self.nbytes()\n" - ] - }, { "data": { "text/plain": [ @@ -7686,7 +7708,7 @@ "Total params: 217\n", "Trainable params: 217\n", "Non-trainable params: 0\n", - "Total mult-adds (M): 1.83\n", + "Total mult-adds (Units.MEGABYTES): 1.83\n", "===================================================================================================================\n", "Input size (MB): 0.11\n", "Forward/backward pass size (MB): 0.86\n", @@ -7710,10 +7732,9 @@ }, { "cell_type": "markdown", - "id": "650e0ec7", + "id": "065db586", "metadata": {}, "source": [ - "\\newpage\n", "We again put the two datasets into a data module, with a\n", "batch size of 64." ] @@ -7721,7 +7742,7 @@ { "cell_type": "code", "execution_count": 105, - "id": "31640121", + "id": "9b871361", "metadata": { "lines_to_next_cell": 0 }, @@ -7736,7 +7757,7 @@ }, { "cell_type": "markdown", - "id": "1de7ae89", + "id": "8e6d61d8", "metadata": {}, "source": [ "We run some data through our model to be sure the sizes match up correctly." @@ -7745,7 +7766,7 @@ { "cell_type": "code", "execution_count": 106, - "id": "af6795f5", + "id": "b63d1f85", "metadata": {}, "outputs": [ { @@ -7768,7 +7789,7 @@ }, { "cell_type": "markdown", - "id": "eecb6d9c", + "id": "7fc69ade", "metadata": {}, "source": [ "We follow our previous example for setting up a trainer for a\n", @@ -7779,7 +7800,7 @@ { "cell_type": "code", "execution_count": 107, - "id": "0d04344c", + "id": "c5f32a4f", "metadata": {}, "outputs": [], "source": [ @@ -7792,7 +7813,7 @@ }, { "cell_type": "markdown", - "id": "9a10444d", + "id": "ed00be6a", "metadata": {}, "source": [ "Fitting the model should by now be familiar.\n", @@ -7802,7 +7823,7 @@ { "cell_type": "code", "execution_count": 108, - "id": "485d7bb1", + "id": "6bd98eb9", "metadata": { "lines_to_next_cell": 2 }, @@ -7811,12 +7832,10 @@ "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", - "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pytorch_lightning/trainer/trainer.py:1789: UserWarning: MPS available but not used. Set `accelerator` and `devices` using `Trainer(accelerator='mps', devices=1)`.\n", - " rank_zero_warn(\n", "\n", " | Name | Type | Params\n", "------------------------------------\n", @@ -7846,7 +7865,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "bf9eb739cc954760813987d94e79fb8e", + "model_id": "d9e7a14d99fa4708bc143ac70d601ad2", "version_major": 2, "version_minor": 0 }, @@ -7942,20 +7961,88 @@ "output_type": "display_data" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + 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"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_loss 0.6207807064056396\n", - " test_r2 0.41084879636764526\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" - ] + "data": { + "text/html": [ + "
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+       "┃   Runningstage.testing    ┃                           ┃\n",
+       "┃          metric           ┃       DataLoader 0        ┃\n",
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+       "│         test_loss         │    0.6186699867248535     │\n",
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The remaining steps are familiar." @@ -9737,7 +10808,7 @@ { "cell_type": "code", "execution_count": 111, - "id": "3cf09a55", + "id": "595df68b", "metadata": {}, "outputs": [], "source": [ @@ -9756,7 +10827,7 @@ { "cell_type": "code", "execution_count": 112, - "id": "930576f3", + "id": "e8142533", "metadata": {}, "outputs": [], "source": [ @@ -9770,7 +10841,7 @@ }, { "cell_type": "markdown", - "id": "a0e3043c", + "id": "86d4e139", "metadata": {}, "source": [ "We continue with the usual training steps, fit the model,\n", @@ -9780,7 +10851,7 @@ { "cell_type": "code", "execution_count": 113, - "id": "b9ae8d0e", + "id": "47bdb236", "metadata": { "lines_to_next_cell": 0 }, @@ -9789,7 +10860,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "GPU available: True (mps), used: False\n", + "GPU available: True (mps), used: True\n", "TPU available: False, using: 0 TPU cores\n", "IPU available: False, using: 0 IPUs\n", "HPU available: False, using: 0 HPUs\n", @@ -9822,7 +10893,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "1e278bfc60e6404f98175752ac8f6482", + "model_id": "adaf10fcbd8c4e5baddfc2ca65d32558", "version_major": 2, "version_minor": 0 }, @@ -9918,20 +10989,116 @@ "output_type": "display_data" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Validation: 0it [00:00, ?it/s]" + ] + }, + "metadata": {}, + "output_type": "display_data" }, { "data": { @@ -10021,34 +11188,52 @@ "name": "stderr", "output_type": "stream", "text": [ - "IOPub message rate exceeded.\n", - "The Jupyter server will temporarily stop sending output\n", - "to the client in order to avoid crashing it.\n", - "To change this limit, set the config variable\n", - "`--ServerApp.iopub_msg_rate_limit`.\n", - "\n", - "Current values:\n", - "ServerApp.iopub_msg_rate_limit=1000.0 (msgs/sec)\n", - "ServerApp.rate_limit_window=3.0 (secs)\n", - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " Test metric DataLoader 0\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n", - " test_loss 0.5648325681686401\n", - " test_r2 0.4639463424682617\n", - "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n" + "`Trainer.fit` stopped: `max_epochs=20` reached.\n" ] }, { "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2666f1d4f060468681384e1b122c9d30", + "version_major": 2, + "version_minor": 0 + }, "text/plain": [ - 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"id": "fd356e46", + "id": "51f435d5", "metadata": {}, "source": [ " \n", @@ -10082,9 +11267,9 @@ "notebook_metadata_filter": "-all" }, "kernelspec": { - "display_name": "Python 3 (ipykernel)", + "display_name": "Python3 (islp_freeze_311)", "language": "python", - "name": "python3" + "name": "islp_freeze_311" }, "language_info": { "codemirror_mode": { @@ -10096,7 +11281,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.17" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/Ch11-surv-lab.ipynb b/Ch11-surv-lab.ipynb index 5ab9f47..efbc233 100644 --- a/Ch11-surv-lab.ipynb +++ b/Ch11-surv-lab.ipynb @@ -34,10 +34,10 @@ "id": "91ac40fd", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:03.064349Z", - "iopub.status.busy": "2023-07-26T05:18:03.064029Z", - "iopub.status.idle": "2023-07-26T05:18:04.312445Z", - "shell.execute_reply": "2023-07-26T05:18:04.312016Z" + "iopub.execute_input": "2023-08-06T17:35:46.303006Z", + "iopub.status.busy": "2023-08-06T17:35:46.302426Z", + "iopub.status.idle": "2023-08-06T17:35:47.388674Z", + "shell.execute_reply": "2023-08-06T17:35:47.388193Z" } }, "outputs": [], @@ -64,10 +64,10 @@ "id": "99782418", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.315115Z", - "iopub.status.busy": "2023-07-26T05:18:04.314859Z", - "iopub.status.idle": "2023-07-26T05:18:04.379768Z", - "shell.execute_reply": "2023-07-26T05:18:04.379303Z" + "iopub.execute_input": "2023-08-06T17:35:47.390741Z", + "iopub.status.busy": "2023-08-06T17:35:47.390555Z", + "iopub.status.idle": "2023-08-06T17:35:47.484777Z", + "shell.execute_reply": "2023-08-06T17:35:47.484422Z" } }, "outputs": [], @@ -97,10 +97,10 @@ "id": "3137149a", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.382594Z", - "iopub.status.busy": "2023-07-26T05:18:04.382386Z", - "iopub.status.idle": "2023-07-26T05:18:04.389761Z", - "shell.execute_reply": "2023-07-26T05:18:04.389375Z" + "iopub.execute_input": "2023-08-06T17:35:47.486501Z", + "iopub.status.busy": "2023-08-06T17:35:47.486385Z", + "iopub.status.idle": "2023-08-06T17:35:47.493362Z", + "shell.execute_reply": "2023-08-06T17:35:47.493058Z" } }, "outputs": [ @@ -135,10 +135,10 @@ "id": "45963c92", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.392289Z", - "iopub.status.busy": "2023-07-26T05:18:04.392117Z", - "iopub.status.idle": "2023-07-26T05:18:04.396285Z", - "shell.execute_reply": "2023-07-26T05:18:04.395840Z" + "iopub.execute_input": "2023-08-06T17:35:47.494963Z", + "iopub.status.busy": "2023-08-06T17:35:47.494863Z", + "iopub.status.idle": "2023-08-06T17:35:47.497996Z", + "shell.execute_reply": "2023-08-06T17:35:47.497741Z" }, "lines_to_next_cell": 2 }, @@ -166,10 +166,10 @@ "id": "73be61f6", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.400201Z", - "iopub.status.busy": "2023-07-26T05:18:04.399975Z", - "iopub.status.idle": "2023-07-26T05:18:04.403967Z", - "shell.execute_reply": "2023-07-26T05:18:04.403581Z" + "iopub.execute_input": "2023-08-06T17:35:47.499414Z", + "iopub.status.busy": "2023-08-06T17:35:47.499312Z", + "iopub.status.idle": "2023-08-06T17:35:47.502029Z", + "shell.execute_reply": "2023-08-06T17:35:47.501779Z" }, "lines_to_next_cell": 2 }, @@ -199,10 +199,10 @@ "id": "572f0b9e", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.406232Z", - "iopub.status.busy": "2023-07-26T05:18:04.406110Z", - "iopub.status.idle": "2023-07-26T05:18:04.409773Z", - "shell.execute_reply": "2023-07-26T05:18:04.409374Z" + "iopub.execute_input": "2023-08-06T17:35:47.503331Z", + "iopub.status.busy": "2023-08-06T17:35:47.503251Z", + "iopub.status.idle": "2023-08-06T17:35:47.506059Z", + "shell.execute_reply": "2023-08-06T17:35:47.505826Z" }, "lines_to_next_cell": 2 }, @@ -255,10 +255,10 @@ "id": "92c39707", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.411840Z", - "iopub.status.busy": "2023-07-26T05:18:04.411663Z", - "iopub.status.idle": "2023-07-26T05:18:04.539774Z", - "shell.execute_reply": "2023-07-26T05:18:04.539439Z" + "iopub.execute_input": "2023-08-06T17:35:47.507415Z", + "iopub.status.busy": "2023-08-06T17:35:47.507329Z", + "iopub.status.idle": "2023-08-06T17:35:47.692016Z", + "shell.execute_reply": "2023-08-06T17:35:47.690384Z" } }, "outputs": [ @@ -321,10 +321,10 @@ "id": "3fc7848c", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.542265Z", - "iopub.status.busy": "2023-07-26T05:18:04.542002Z", - "iopub.status.idle": "2023-07-26T05:18:04.674613Z", - "shell.execute_reply": "2023-07-26T05:18:04.674126Z" + "iopub.execute_input": "2023-08-06T17:35:47.696231Z", + "iopub.status.busy": "2023-08-06T17:35:47.695950Z", + "iopub.status.idle": "2023-08-06T17:35:47.857113Z", + "shell.execute_reply": "2023-08-06T17:35:47.856731Z" } }, "outputs": [ @@ -366,10 +366,10 @@ "id": "bf30d26f", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.679625Z", - "iopub.status.busy": "2023-07-26T05:18:04.679410Z", - "iopub.status.idle": "2023-07-26T05:18:04.743501Z", - "shell.execute_reply": "2023-07-26T05:18:04.743166Z" + "iopub.execute_input": "2023-08-06T17:35:47.858891Z", + "iopub.status.busy": "2023-08-06T17:35:47.858766Z", + "iopub.status.idle": "2023-08-06T17:35:47.913319Z", + "shell.execute_reply": "2023-08-06T17:35:47.913028Z" }, "lines_to_next_cell": 2 }, @@ -479,10 +479,10 @@ "id": "2ab78e07", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.746088Z", - "iopub.status.busy": "2023-07-26T05:18:04.745814Z", - "iopub.status.idle": "2023-07-26T05:18:04.773972Z", - "shell.execute_reply": "2023-07-26T05:18:04.773498Z" + "iopub.execute_input": "2023-08-06T17:35:47.914969Z", + "iopub.status.busy": "2023-08-06T17:35:47.914826Z", + "iopub.status.idle": "2023-08-06T17:35:47.941528Z", + "shell.execute_reply": "2023-08-06T17:35:47.941277Z" } }, "outputs": [ @@ -572,10 +572,10 @@ "id": "4716b7b0", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.776775Z", - "iopub.status.busy": "2023-07-26T05:18:04.776463Z", - "iopub.status.idle": "2023-07-26T05:18:04.783362Z", - "shell.execute_reply": "2023-07-26T05:18:04.782865Z" + "iopub.execute_input": "2023-08-06T17:35:47.943061Z", + "iopub.status.busy": "2023-08-06T17:35:47.942963Z", + "iopub.status.idle": "2023-08-06T17:35:47.948065Z", + "shell.execute_reply": "2023-08-06T17:35:47.947785Z" } }, "outputs": [ @@ -678,10 +678,10 @@ "id": "c2767d88", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.785790Z", - "iopub.status.busy": "2023-07-26T05:18:04.785586Z", - "iopub.status.idle": "2023-07-26T05:18:04.824235Z", - "shell.execute_reply": "2023-07-26T05:18:04.823739Z" + "iopub.execute_input": "2023-08-06T17:35:47.949725Z", + "iopub.status.busy": "2023-08-06T17:35:47.949641Z", + "iopub.status.idle": "2023-08-06T17:35:47.982167Z", + "shell.execute_reply": "2023-08-06T17:35:47.981821Z" } }, "outputs": [ @@ -826,10 +826,10 @@ "id": "ede1d219", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.826852Z", - "iopub.status.busy": "2023-07-26T05:18:04.826662Z", - "iopub.status.idle": "2023-07-26T05:18:04.831013Z", - "shell.execute_reply": "2023-07-26T05:18:04.830464Z" + "iopub.execute_input": "2023-08-06T17:35:47.983958Z", + "iopub.status.busy": "2023-08-06T17:35:47.983832Z", + "iopub.status.idle": "2023-08-06T17:35:47.989895Z", + "shell.execute_reply": "2023-08-06T17:35:47.989591Z" } }, "outputs": [], @@ -859,10 +859,10 @@ "id": "dc032a71", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.833522Z", - "iopub.status.busy": "2023-07-26T05:18:04.833389Z", - "iopub.status.idle": "2023-07-26T05:18:04.840549Z", - "shell.execute_reply": "2023-07-26T05:18:04.840260Z" + "iopub.execute_input": "2023-08-06T17:35:47.991841Z", + "iopub.status.busy": "2023-08-06T17:35:47.991705Z", + "iopub.status.idle": "2023-08-06T17:35:47.997910Z", + "shell.execute_reply": "2023-08-06T17:35:47.997622Z" } }, "outputs": [ @@ -987,10 +987,10 @@ "id": "e7c1fe43", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.843157Z", - "iopub.status.busy": "2023-07-26T05:18:04.843004Z", - "iopub.status.idle": "2023-07-26T05:18:04.852876Z", - "shell.execute_reply": "2023-07-26T05:18:04.852545Z" + "iopub.execute_input": "2023-08-06T17:35:47.999542Z", + "iopub.status.busy": "2023-08-06T17:35:47.999430Z", + "iopub.status.idle": "2023-08-06T17:35:48.007263Z", + "shell.execute_reply": "2023-08-06T17:35:48.006958Z" } }, "outputs": [ @@ -1129,10 +1129,10 @@ "id": "f89fbed7", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.855400Z", - "iopub.status.busy": "2023-07-26T05:18:04.855197Z", - "iopub.status.idle": "2023-07-26T05:18:04.864584Z", - "shell.execute_reply": "2023-07-26T05:18:04.864194Z" + "iopub.execute_input": "2023-08-06T17:35:48.008740Z", + "iopub.status.busy": "2023-08-06T17:35:48.008640Z", + "iopub.status.idle": "2023-08-06T17:35:48.015006Z", + "shell.execute_reply": "2023-08-06T17:35:48.014745Z" }, "lines_to_next_cell": 0 }, @@ -1290,10 +1290,10 @@ "id": "8f0329b4", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.867553Z", - "iopub.status.busy": "2023-07-26T05:18:04.867105Z", - "iopub.status.idle": "2023-07-26T05:18:04.987503Z", - "shell.execute_reply": "2023-07-26T05:18:04.986681Z" + "iopub.execute_input": "2023-08-06T17:35:48.016512Z", + "iopub.status.busy": "2023-08-06T17:35:48.016391Z", + "iopub.status.idle": "2023-08-06T17:35:48.128436Z", + "shell.execute_reply": "2023-08-06T17:35:48.127998Z" }, "lines_to_next_cell": 2 }, @@ -1333,10 +1333,10 @@ "id": "3045bfc0", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:04.990450Z", - "iopub.status.busy": "2023-07-26T05:18:04.990225Z", - "iopub.status.idle": "2023-07-26T05:18:05.181343Z", - "shell.execute_reply": "2023-07-26T05:18:05.178676Z" + "iopub.execute_input": "2023-08-06T17:35:48.130335Z", + "iopub.status.busy": "2023-08-06T17:35:48.130198Z", + "iopub.status.idle": "2023-08-06T17:35:48.248098Z", + "shell.execute_reply": "2023-08-06T17:35:48.247765Z" } }, "outputs": [ @@ -1378,10 +1378,10 @@ "id": "d070f716", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.184743Z", - "iopub.status.busy": "2023-07-26T05:18:05.184569Z", - "iopub.status.idle": "2023-07-26T05:18:05.222538Z", - "shell.execute_reply": "2023-07-26T05:18:05.221996Z" + "iopub.execute_input": "2023-08-06T17:35:48.249785Z", + "iopub.status.busy": "2023-08-06T17:35:48.249668Z", + "iopub.status.idle": "2023-08-06T17:35:48.282954Z", + "shell.execute_reply": "2023-08-06T17:35:48.282630Z" }, "lines_to_next_cell": 2 }, @@ -1467,10 +1467,10 @@ "id": "2bbcdd0c", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.225196Z", - "iopub.status.busy": "2023-07-26T05:18:05.224969Z", - "iopub.status.idle": "2023-07-26T05:18:05.270258Z", - "shell.execute_reply": "2023-07-26T05:18:05.269721Z" + "iopub.execute_input": "2023-08-06T17:35:48.284714Z", + "iopub.status.busy": "2023-08-06T17:35:48.284593Z", + "iopub.status.idle": "2023-08-06T17:35:48.323890Z", + "shell.execute_reply": "2023-08-06T17:35:48.323545Z" } }, "outputs": [ @@ -1611,10 +1611,10 @@ "id": "b8ece43a", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.272852Z", - "iopub.status.busy": "2023-07-26T05:18:05.272613Z", - "iopub.status.idle": "2023-07-26T05:18:05.277670Z", - "shell.execute_reply": "2023-07-26T05:18:05.277169Z" + "iopub.execute_input": "2023-08-06T17:35:48.325634Z", + "iopub.status.busy": "2023-08-06T17:35:48.325517Z", + "iopub.status.idle": "2023-08-06T17:35:48.329272Z", + "shell.execute_reply": "2023-08-06T17:35:48.328978Z" } }, "outputs": [], @@ -1649,10 +1649,10 @@ "id": "3e4f766f", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.279951Z", - "iopub.status.busy": "2023-07-26T05:18:05.279774Z", - "iopub.status.idle": "2023-07-26T05:18:05.289519Z", - "shell.execute_reply": "2023-07-26T05:18:05.288948Z" + "iopub.execute_input": "2023-08-06T17:35:48.330871Z", + "iopub.status.busy": "2023-08-06T17:35:48.330782Z", + "iopub.status.idle": "2023-08-06T17:35:48.337958Z", + "shell.execute_reply": "2023-08-06T17:35:48.337672Z" } }, "outputs": [], @@ -1681,10 +1681,10 @@ "id": "72f42d14", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.292713Z", - "iopub.status.busy": "2023-07-26T05:18:05.292424Z", - "iopub.status.idle": "2023-07-26T05:18:05.299084Z", - "shell.execute_reply": "2023-07-26T05:18:05.298414Z" + "iopub.execute_input": "2023-08-06T17:35:48.339669Z", + "iopub.status.busy": "2023-08-06T17:35:48.339578Z", + "iopub.status.idle": "2023-08-06T17:35:48.343948Z", + "shell.execute_reply": "2023-08-06T17:35:48.343688Z" } }, "outputs": [ @@ -1793,10 +1793,10 @@ "id": "8b921536", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.301800Z", - "iopub.status.busy": "2023-07-26T05:18:05.301580Z", - "iopub.status.idle": "2023-07-26T05:18:05.340807Z", - "shell.execute_reply": "2023-07-26T05:18:05.311843Z" + "iopub.execute_input": "2023-08-06T17:35:48.345389Z", + "iopub.status.busy": "2023-08-06T17:35:48.345291Z", + "iopub.status.idle": "2023-08-06T17:35:48.350596Z", + "shell.execute_reply": "2023-08-06T17:35:48.349892Z" } }, "outputs": [], @@ -1840,10 +1840,10 @@ "id": "96ce0f99", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.399214Z", - "iopub.status.busy": "2023-07-26T05:18:05.386941Z", - "iopub.status.idle": "2023-07-26T05:18:05.423513Z", - "shell.execute_reply": "2023-07-26T05:18:05.417411Z" + "iopub.execute_input": "2023-08-06T17:35:48.356110Z", + "iopub.status.busy": "2023-08-06T17:35:48.355787Z", + "iopub.status.idle": "2023-08-06T17:35:48.360120Z", + "shell.execute_reply": "2023-08-06T17:35:48.358812Z" }, "lines_to_next_cell": 0 }, @@ -1871,10 +1871,10 @@ "id": "63d78ff9", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.450050Z", - "iopub.status.busy": "2023-07-26T05:18:05.449814Z", - "iopub.status.idle": "2023-07-26T05:18:05.587170Z", - "shell.execute_reply": "2023-07-26T05:18:05.586673Z" + "iopub.execute_input": "2023-08-06T17:35:48.363547Z", + "iopub.status.busy": "2023-08-06T17:35:48.363232Z", + "iopub.status.idle": "2023-08-06T17:35:48.547724Z", + "shell.execute_reply": "2023-08-06T17:35:48.547018Z" } }, "outputs": [], @@ -1900,10 +1900,10 @@ "id": "fe008dbf", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.590252Z", - "iopub.status.busy": "2023-07-26T05:18:05.589902Z", - "iopub.status.idle": "2023-07-26T05:18:05.596018Z", - "shell.execute_reply": "2023-07-26T05:18:05.595604Z" + "iopub.execute_input": "2023-08-06T17:35:48.552971Z", + "iopub.status.busy": "2023-08-06T17:35:48.552635Z", + "iopub.status.idle": "2023-08-06T17:35:48.584979Z", + "shell.execute_reply": "2023-08-06T17:35:48.563731Z" }, "lines_to_next_cell": 2 }, @@ -2008,10 +2008,10 @@ "id": "c3a2bec7", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.598122Z", - "iopub.status.busy": "2023-07-26T05:18:05.597969Z", - "iopub.status.idle": "2023-07-26T05:18:05.601009Z", - "shell.execute_reply": "2023-07-26T05:18:05.600579Z" + "iopub.execute_input": "2023-08-06T17:35:48.615161Z", + "iopub.status.busy": "2023-08-06T17:35:48.614999Z", + "iopub.status.idle": "2023-08-06T17:35:48.618097Z", + "shell.execute_reply": "2023-08-06T17:35:48.617615Z" } }, "outputs": [ @@ -2044,10 +2044,10 @@ "id": "2b27af56", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.603318Z", - "iopub.status.busy": "2023-07-26T05:18:05.603142Z", - "iopub.status.idle": "2023-07-26T05:18:05.827076Z", - "shell.execute_reply": "2023-07-26T05:18:05.826151Z" + "iopub.execute_input": "2023-08-06T17:35:48.620507Z", + "iopub.status.busy": "2023-08-06T17:35:48.620371Z", + "iopub.status.idle": "2023-08-06T17:35:48.790525Z", + "shell.execute_reply": "2023-08-06T17:35:48.790116Z" } }, "outputs": [ @@ -2096,10 +2096,10 @@ "id": "9625598d", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:05.830554Z", - "iopub.status.busy": "2023-07-26T05:18:05.830059Z", - "iopub.status.idle": "2023-07-26T05:18:06.008529Z", - "shell.execute_reply": "2023-07-26T05:18:06.008079Z" + "iopub.execute_input": "2023-08-06T17:35:48.792256Z", + "iopub.status.busy": "2023-08-06T17:35:48.792159Z", + "iopub.status.idle": "2023-08-06T17:35:49.004599Z", + "shell.execute_reply": "2023-08-06T17:35:49.004246Z" } }, "outputs": [ @@ -2152,10 +2152,10 @@ "id": "75a744ef", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:06.012649Z", - "iopub.status.busy": "2023-07-26T05:18:06.012037Z", - "iopub.status.idle": "2023-07-26T05:18:06.033832Z", - "shell.execute_reply": "2023-07-26T05:18:06.033320Z" + "iopub.execute_input": "2023-08-06T17:35:49.006368Z", + "iopub.status.busy": "2023-08-06T17:35:49.006251Z", + "iopub.status.idle": "2023-08-06T17:35:49.026122Z", + "shell.execute_reply": "2023-08-06T17:35:49.025786Z" }, "lines_to_next_cell": 2 }, @@ -2259,10 +2259,10 @@ "id": "9badb3e3", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:06.036375Z", - "iopub.status.busy": "2023-07-26T05:18:06.036170Z", - "iopub.status.idle": "2023-07-26T05:18:06.055850Z", - "shell.execute_reply": "2023-07-26T05:18:06.055183Z" + "iopub.execute_input": "2023-08-06T17:35:49.027909Z", + "iopub.status.busy": "2023-08-06T17:35:49.027782Z", + "iopub.status.idle": "2023-08-06T17:35:49.046955Z", + "shell.execute_reply": "2023-08-06T17:35:49.046606Z" }, "lines_to_next_cell": 2 }, @@ -2369,10 +2369,10 @@ "id": "026e9ff8", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:06.058057Z", - "iopub.status.busy": "2023-07-26T05:18:06.057906Z", - "iopub.status.idle": "2023-07-26T05:18:06.184883Z", - "shell.execute_reply": "2023-07-26T05:18:06.184356Z" + "iopub.execute_input": "2023-08-06T17:35:49.048485Z", + "iopub.status.busy": "2023-08-06T17:35:49.048378Z", + "iopub.status.idle": "2023-08-06T17:35:49.175538Z", + "shell.execute_reply": "2023-08-06T17:35:49.175268Z" }, "lines_to_next_cell": 2 }, @@ -2474,10 +2474,10 @@ "id": "7cab3789", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:06.187428Z", - "iopub.status.busy": "2023-07-26T05:18:06.187255Z", - "iopub.status.idle": "2023-07-26T05:18:06.315832Z", - "shell.execute_reply": "2023-07-26T05:18:06.314374Z" + "iopub.execute_input": "2023-08-06T17:35:49.177180Z", + "iopub.status.busy": "2023-08-06T17:35:49.177056Z", + "iopub.status.idle": "2023-08-06T17:35:49.306158Z", + "shell.execute_reply": "2023-08-06T17:35:49.305806Z" }, "lines_to_next_cell": 2 }, @@ -2582,10 +2582,10 @@ "id": "5cc4b898", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:06.320288Z", - "iopub.status.busy": "2023-07-26T05:18:06.319261Z", - "iopub.status.idle": "2023-07-26T05:18:06.585074Z", - "shell.execute_reply": "2023-07-26T05:18:06.577564Z" + "iopub.execute_input": "2023-08-06T17:35:49.308130Z", + "iopub.status.busy": "2023-08-06T17:35:49.307985Z", + "iopub.status.idle": "2023-08-06T17:35:49.596821Z", + "shell.execute_reply": "2023-08-06T17:35:49.585317Z" }, "lines_to_next_cell": 2 }, @@ -2716,7 +2716,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.17" + "version": "3.11.4" } }, "nbformat": 4, diff --git a/Ch12-unsup-lab.ipynb b/Ch12-unsup-lab.ipynb index d76363d..030e9f3 100644 --- a/Ch12-unsup-lab.ipynb +++ b/Ch12-unsup-lab.ipynb @@ -22,10 +22,10 @@ "id": "24559be0", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:08.163850Z", - "iopub.status.busy": "2023-07-26T05:18:08.163726Z", - "iopub.status.idle": "2023-07-26T05:18:09.209261Z", - "shell.execute_reply": "2023-07-26T05:18:09.208715Z" + "iopub.execute_input": "2023-08-06T17:35:50.946303Z", + "iopub.status.busy": "2023-08-06T17:35:50.945891Z", + "iopub.status.idle": "2023-08-06T17:35:51.937962Z", + "shell.execute_reply": "2023-08-06T17:35:51.937388Z" }, "lines_to_next_cell": 0 }, @@ -55,10 +55,10 @@ "id": "06fff57d", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:09.212356Z", - "iopub.status.busy": "2023-07-26T05:18:09.212070Z", - "iopub.status.idle": "2023-07-26T05:18:09.327611Z", - "shell.execute_reply": "2023-07-26T05:18:09.327246Z" + "iopub.execute_input": "2023-08-06T17:35:51.940380Z", + "iopub.status.busy": "2023-08-06T17:35:51.940035Z", + "iopub.status.idle": "2023-08-06T17:35:52.182557Z", + "shell.execute_reply": "2023-08-06T17:35:52.182174Z" } }, "outputs": [], @@ -92,10 +92,10 @@ "id": "f425e07e", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:09.329909Z", - "iopub.status.busy": "2023-07-26T05:18:09.329763Z", - "iopub.status.idle": "2023-07-26T05:18:10.559326Z", - "shell.execute_reply": "2023-07-26T05:18:10.558692Z" + "iopub.execute_input": "2023-08-06T17:35:52.184517Z", + "iopub.status.busy": "2023-08-06T17:35:52.184399Z", + "iopub.status.idle": "2023-08-06T17:35:53.499360Z", + "shell.execute_reply": "2023-08-06T17:35:53.498788Z" } }, "outputs": [ @@ -559,10 +559,10 @@ "id": "b127d014", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.561457Z", - "iopub.status.busy": "2023-07-26T05:18:10.561326Z", - "iopub.status.idle": "2023-07-26T05:18:10.564289Z", - "shell.execute_reply": "2023-07-26T05:18:10.563966Z" + "iopub.execute_input": "2023-08-06T17:35:53.502695Z", + "iopub.status.busy": "2023-08-06T17:35:53.502469Z", + "iopub.status.idle": "2023-08-06T17:35:53.506258Z", + "shell.execute_reply": "2023-08-06T17:35:53.505850Z" } }, "outputs": [ @@ -595,10 +595,10 @@ "id": "c7343f72", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.566649Z", - "iopub.status.busy": "2023-07-26T05:18:10.566503Z", - "iopub.status.idle": "2023-07-26T05:18:10.570319Z", - "shell.execute_reply": "2023-07-26T05:18:10.569890Z" + "iopub.execute_input": "2023-08-06T17:35:53.508693Z", + "iopub.status.busy": "2023-08-06T17:35:53.508529Z", + "iopub.status.idle": "2023-08-06T17:35:53.513068Z", + "shell.execute_reply": "2023-08-06T17:35:53.512687Z" }, "lines_to_next_cell": 2 }, @@ -638,10 +638,10 @@ "id": "34501140", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.572610Z", - "iopub.status.busy": "2023-07-26T05:18:10.572485Z", - "iopub.status.idle": "2023-07-26T05:18:10.575894Z", - "shell.execute_reply": "2023-07-26T05:18:10.575543Z" + "iopub.execute_input": "2023-08-06T17:35:53.515314Z", + "iopub.status.busy": "2023-08-06T17:35:53.515139Z", + "iopub.status.idle": "2023-08-06T17:35:53.518912Z", + "shell.execute_reply": "2023-08-06T17:35:53.518569Z" } }, "outputs": [ @@ -692,10 +692,10 @@ "id": "daf119e8", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.578199Z", - "iopub.status.busy": "2023-07-26T05:18:10.578025Z", - "iopub.status.idle": "2023-07-26T05:18:10.581928Z", - "shell.execute_reply": "2023-07-26T05:18:10.581446Z" + "iopub.execute_input": "2023-08-06T17:35:53.521091Z", + "iopub.status.busy": "2023-08-06T17:35:53.520960Z", + "iopub.status.idle": "2023-08-06T17:35:53.525175Z", + "shell.execute_reply": "2023-08-06T17:35:53.524847Z" }, "lines_to_next_cell": 0 }, @@ -722,10 +722,10 @@ "id": "a0eda7c9", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.584181Z", - "iopub.status.busy": "2023-07-26T05:18:10.584070Z", - "iopub.status.idle": "2023-07-26T05:18:10.586440Z", - "shell.execute_reply": "2023-07-26T05:18:10.586052Z" + "iopub.execute_input": "2023-08-06T17:35:53.527052Z", + "iopub.status.busy": "2023-08-06T17:35:53.526916Z", + "iopub.status.idle": "2023-08-06T17:35:53.528807Z", + "shell.execute_reply": "2023-08-06T17:35:53.528507Z" }, "lines_to_next_cell": 0 }, @@ -751,17 +751,17 @@ "id": "1430fb3c", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.588957Z", - "iopub.status.busy": "2023-07-26T05:18:10.588809Z", - "iopub.status.idle": "2023-07-26T05:18:10.593315Z", - "shell.execute_reply": "2023-07-26T05:18:10.592971Z" + "iopub.execute_input": "2023-08-06T17:35:53.530511Z", + "iopub.status.busy": "2023-08-06T17:35:53.530398Z", + "iopub.status.idle": "2023-08-06T17:35:53.534557Z", + "shell.execute_reply": "2023-08-06T17:35:53.534277Z" } }, "outputs": [ { "data": { "text/html": [ - "
PCA()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + "
PCA()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "PCA()" @@ -792,10 +792,10 @@ "id": "6131d8d1", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.595542Z", - "iopub.status.busy": "2023-07-26T05:18:10.595388Z", - "iopub.status.idle": "2023-07-26T05:18:10.598527Z", - "shell.execute_reply": "2023-07-26T05:18:10.598057Z" + "iopub.execute_input": "2023-08-06T17:35:53.536106Z", + "iopub.status.busy": "2023-08-06T17:35:53.536010Z", + "iopub.status.idle": "2023-08-06T17:35:53.538352Z", + "shell.execute_reply": "2023-08-06T17:35:53.538107Z" } }, "outputs": [ @@ -829,10 +829,10 @@ "id": "08246aad", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.600656Z", - "iopub.status.busy": "2023-07-26T05:18:10.600536Z", - "iopub.status.idle": "2023-07-26T05:18:10.603024Z", - "shell.execute_reply": "2023-07-26T05:18:10.602498Z" + "iopub.execute_input": "2023-08-06T17:35:53.539900Z", + "iopub.status.busy": "2023-08-06T17:35:53.539817Z", + "iopub.status.idle": "2023-08-06T17:35:53.541716Z", + "shell.execute_reply": "2023-08-06T17:35:53.541426Z" }, "lines_to_next_cell": 0 }, @@ -858,10 +858,10 @@ "id": "b682b632", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.605166Z", - "iopub.status.busy": "2023-07-26T05:18:10.605000Z", - "iopub.status.idle": "2023-07-26T05:18:10.607923Z", - "shell.execute_reply": "2023-07-26T05:18:10.607498Z" + "iopub.execute_input": "2023-08-06T17:35:53.543126Z", + "iopub.status.busy": "2023-08-06T17:35:53.543023Z", + "iopub.status.idle": "2023-08-06T17:35:53.545038Z", + "shell.execute_reply": "2023-08-06T17:35:53.544799Z" } }, "outputs": [ @@ -901,10 +901,10 @@ "id": "c165e990", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.610624Z", - "iopub.status.busy": "2023-07-26T05:18:10.610442Z", - "iopub.status.idle": "2023-07-26T05:18:10.736284Z", - "shell.execute_reply": "2023-07-26T05:18:10.735735Z" + "iopub.execute_input": "2023-08-06T17:35:53.546528Z", + "iopub.status.busy": "2023-08-06T17:35:53.546434Z", + "iopub.status.idle": "2023-08-06T17:35:53.703738Z", + "shell.execute_reply": "2023-08-06T17:35:53.701839Z" }, "lines_to_next_cell": 0 }, @@ -951,10 +951,10 @@ "id": "848c9f35", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.738926Z", - "iopub.status.busy": "2023-07-26T05:18:10.738771Z", - "iopub.status.idle": "2023-07-26T05:18:10.848441Z", - "shell.execute_reply": "2023-07-26T05:18:10.847972Z" + "iopub.execute_input": "2023-08-06T17:35:53.707901Z", + "iopub.status.busy": "2023-08-06T17:35:53.707587Z", + "iopub.status.idle": "2023-08-06T17:35:53.873714Z", + "shell.execute_reply": "2023-08-06T17:35:53.873405Z" } }, "outputs": [ @@ -998,10 +998,10 @@ "id": "34fdfe21", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.852220Z", - "iopub.status.busy": "2023-07-26T05:18:10.851752Z", - "iopub.status.idle": "2023-07-26T05:18:10.859190Z", - "shell.execute_reply": "2023-07-26T05:18:10.857389Z" + "iopub.execute_input": "2023-08-06T17:35:53.875331Z", + "iopub.status.busy": "2023-08-06T17:35:53.875218Z", + "iopub.status.idle": "2023-08-06T17:35:53.877664Z", + "shell.execute_reply": "2023-08-06T17:35:53.877409Z" }, "lines_to_next_cell": 2 }, @@ -1036,10 +1036,10 @@ "id": "31b43c57", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.861366Z", - "iopub.status.busy": "2023-07-26T05:18:10.861239Z", - "iopub.status.idle": "2023-07-26T05:18:10.864540Z", - "shell.execute_reply": "2023-07-26T05:18:10.863998Z" + "iopub.execute_input": "2023-08-06T17:35:53.879208Z", + "iopub.status.busy": "2023-08-06T17:35:53.879107Z", + "iopub.status.idle": "2023-08-06T17:35:53.881162Z", + "shell.execute_reply": "2023-08-06T17:35:53.880912Z" }, "lines_to_next_cell": 0 }, @@ -1074,10 +1074,10 @@ "id": "68e47d3a", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.867030Z", - "iopub.status.busy": "2023-07-26T05:18:10.866863Z", - "iopub.status.idle": "2023-07-26T05:18:10.869949Z", - "shell.execute_reply": "2023-07-26T05:18:10.869455Z" + "iopub.execute_input": "2023-08-06T17:35:53.882669Z", + "iopub.status.busy": "2023-08-06T17:35:53.882569Z", + "iopub.status.idle": "2023-08-06T17:35:53.884536Z", + "shell.execute_reply": "2023-08-06T17:35:53.884304Z" }, "lines_to_next_cell": 0 }, @@ -1115,10 +1115,10 @@ "id": "e87fe198", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:10.872333Z", - "iopub.status.busy": "2023-07-26T05:18:10.872213Z", - "iopub.status.idle": "2023-07-26T05:18:11.030288Z", - "shell.execute_reply": "2023-07-26T05:18:11.029440Z" + "iopub.execute_input": "2023-08-06T17:35:53.885937Z", + "iopub.status.busy": "2023-08-06T17:35:53.885846Z", + "iopub.status.idle": "2023-08-06T17:35:54.017444Z", + "shell.execute_reply": "2023-08-06T17:35:54.017056Z" }, "lines_to_next_cell": 0 }, @@ -1151,10 +1151,10 @@ "id": "409fb0c6", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.033250Z", - "iopub.status.busy": "2023-07-26T05:18:11.033097Z", - "iopub.status.idle": "2023-07-26T05:18:11.153804Z", - "shell.execute_reply": "2023-07-26T05:18:11.153245Z" + "iopub.execute_input": "2023-08-06T17:35:54.019369Z", + "iopub.status.busy": "2023-08-06T17:35:54.019233Z", + "iopub.status.idle": "2023-08-06T17:35:54.126102Z", + "shell.execute_reply": "2023-08-06T17:35:54.125778Z" }, "lines_to_next_cell": 0 }, @@ -1199,10 +1199,10 @@ "id": "e563e41b", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.157597Z", - "iopub.status.busy": "2023-07-26T05:18:11.157216Z", - "iopub.status.idle": "2023-07-26T05:18:11.162432Z", - "shell.execute_reply": "2023-07-26T05:18:11.162026Z" + "iopub.execute_input": "2023-08-06T17:35:54.128000Z", + "iopub.status.busy": "2023-08-06T17:35:54.127867Z", + "iopub.status.idle": "2023-08-06T17:35:54.130547Z", + "shell.execute_reply": "2023-08-06T17:35:54.130247Z" }, "lines_to_next_cell": 0 }, @@ -1248,10 +1248,10 @@ "id": "f83ad0bc", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.164364Z", - "iopub.status.busy": "2023-07-26T05:18:11.164225Z", - "iopub.status.idle": "2023-07-26T05:18:11.167031Z", - "shell.execute_reply": "2023-07-26T05:18:11.166724Z" + "iopub.execute_input": "2023-08-06T17:35:54.132102Z", + "iopub.status.busy": "2023-08-06T17:35:54.131992Z", + "iopub.status.idle": "2023-08-06T17:35:54.134511Z", + "shell.execute_reply": "2023-08-06T17:35:54.134231Z" }, "lines_to_next_cell": 0 }, @@ -1289,10 +1289,10 @@ "id": "cb9bdc46", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.169269Z", - "iopub.status.busy": "2023-07-26T05:18:11.169096Z", - "iopub.status.idle": "2023-07-26T05:18:11.172167Z", - "shell.execute_reply": "2023-07-26T05:18:11.171624Z" + "iopub.execute_input": "2023-08-06T17:35:54.135963Z", + "iopub.status.busy": "2023-08-06T17:35:54.135871Z", + "iopub.status.idle": "2023-08-06T17:35:54.138169Z", + "shell.execute_reply": "2023-08-06T17:35:54.137815Z" } }, "outputs": [ @@ -1300,8 +1300,8 @@ "data": { "text/plain": [ "array([[-0.53589947, -0.58318363, -0.27819087, -0.54343209],\n", - " [ 0.41818087, 0.1879856 , -0.87280619, -0.16731864],\n", - " [-0.34123273, -0.26814843, -0.37801579, 0.81777791],\n", + " [-0.41818087, -0.1879856 , 0.87280619, 0.16731864],\n", + " [ 0.34123273, 0.26814843, 0.37801579, -0.81777791],\n", " [ 0.6492278 , -0.74340748, 0.13387773, 0.08902432]])" ] }, @@ -1320,10 +1320,10 @@ "id": "f23c101e", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.174404Z", - "iopub.status.busy": "2023-07-26T05:18:11.174265Z", - "iopub.status.idle": "2023-07-26T05:18:11.177096Z", - "shell.execute_reply": "2023-07-26T05:18:11.176712Z" + "iopub.execute_input": "2023-08-06T17:35:54.139741Z", + "iopub.status.busy": "2023-08-06T17:35:54.139635Z", + "iopub.status.idle": "2023-08-06T17:35:54.141804Z", + "shell.execute_reply": "2023-08-06T17:35:54.141560Z" }, "lines_to_next_cell": 0 }, @@ -1360,19 +1360,19 @@ "id": "4cc49622", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.179219Z", - "iopub.status.busy": "2023-07-26T05:18:11.179054Z", - "iopub.status.idle": "2023-07-26T05:18:11.182070Z", - "shell.execute_reply": "2023-07-26T05:18:11.181699Z" + "iopub.execute_input": "2023-08-06T17:35:54.143256Z", + "iopub.status.busy": "2023-08-06T17:35:54.143161Z", + "iopub.status.idle": "2023-08-06T17:35:54.145229Z", + "shell.execute_reply": "2023-08-06T17:35:54.144969Z" } }, "outputs": [ { "data": { "text/plain": [ - "array([[-0.98556588, 1.13339238, -0.44426879, 0.15626714],\n", - " [-1.95013775, 1.07321326, 2.04000333, -0.43858344],\n", - " [-1.76316354, -0.74595678, 0.05478082, -0.83465292]])" + "array([[-0.98556588, -1.13339238, 0.44426879, 0.15626714],\n", + " [-1.95013775, -1.07321326, -2.04000333, -0.43858344],\n", + " [-1.76316354, 0.74595678, -0.05478082, -0.83465292]])" ] }, "execution_count": 24, @@ -1390,10 +1390,10 @@ "id": "c96c9fe1", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.184051Z", - "iopub.status.busy": "2023-07-26T05:18:11.183934Z", - "iopub.status.idle": "2023-07-26T05:18:11.186945Z", - "shell.execute_reply": "2023-07-26T05:18:11.186473Z" + "iopub.execute_input": "2023-08-06T17:35:54.146759Z", + "iopub.status.busy": "2023-08-06T17:35:54.146653Z", + "iopub.status.idle": "2023-08-06T17:35:54.148887Z", + "shell.execute_reply": "2023-08-06T17:35:54.148630Z" }, "lines_to_next_cell": 0 }, @@ -1435,10 +1435,10 @@ "id": "574409d6", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.189376Z", - "iopub.status.busy": "2023-07-26T05:18:11.189199Z", - "iopub.status.idle": "2023-07-26T05:18:11.192254Z", - "shell.execute_reply": "2023-07-26T05:18:11.191873Z" + "iopub.execute_input": "2023-08-06T17:35:54.150348Z", + "iopub.status.busy": "2023-08-06T17:35:54.150251Z", + "iopub.status.idle": "2023-08-06T17:35:54.152569Z", + "shell.execute_reply": "2023-08-06T17:35:54.152331Z" } }, "outputs": [], @@ -1475,10 +1475,10 @@ "id": "89f190ae", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.194569Z", - "iopub.status.busy": "2023-07-26T05:18:11.194458Z", - "iopub.status.idle": "2023-07-26T05:18:11.197204Z", - "shell.execute_reply": "2023-07-26T05:18:11.196762Z" + "iopub.execute_input": "2023-08-06T17:35:54.154068Z", + "iopub.status.busy": "2023-08-06T17:35:54.153976Z", + "iopub.status.idle": "2023-08-06T17:35:54.155943Z", + "shell.execute_reply": "2023-08-06T17:35:54.155667Z" }, "lines_to_next_cell": 0 }, @@ -1508,10 +1508,10 @@ "id": "322f339c", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.199355Z", - "iopub.status.busy": "2023-07-26T05:18:11.199208Z", - "iopub.status.idle": "2023-07-26T05:18:11.201784Z", - "shell.execute_reply": "2023-07-26T05:18:11.201348Z" + "iopub.execute_input": "2023-08-06T17:35:54.157547Z", + "iopub.status.busy": "2023-08-06T17:35:54.157431Z", + "iopub.status.idle": "2023-08-06T17:35:54.159402Z", + "shell.execute_reply": "2023-08-06T17:35:54.159143Z" } }, "outputs": [], @@ -1536,10 +1536,10 @@ "id": "7e106d1a", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.204020Z", - "iopub.status.busy": "2023-07-26T05:18:11.203890Z", - "iopub.status.idle": "2023-07-26T05:18:11.206286Z", - "shell.execute_reply": "2023-07-26T05:18:11.205915Z" + "iopub.execute_input": "2023-08-06T17:35:54.160950Z", + "iopub.status.busy": "2023-08-06T17:35:54.160834Z", + "iopub.status.idle": "2023-08-06T17:35:54.162815Z", + "shell.execute_reply": "2023-08-06T17:35:54.162552Z" }, "lines_to_next_cell": 0 }, @@ -1576,10 +1576,10 @@ "id": "7cb05ce4", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.208518Z", - "iopub.status.busy": "2023-07-26T05:18:11.208345Z", - "iopub.status.idle": "2023-07-26T05:18:11.212476Z", - "shell.execute_reply": "2023-07-26T05:18:11.211847Z" + "iopub.execute_input": "2023-08-06T17:35:54.164360Z", + "iopub.status.busy": "2023-08-06T17:35:54.164263Z", + "iopub.status.idle": "2023-08-06T17:35:54.167306Z", + "shell.execute_reply": "2023-08-06T17:35:54.167033Z" } }, "outputs": [ @@ -1631,10 +1631,10 @@ "id": "6f245188", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.214882Z", - "iopub.status.busy": "2023-07-26T05:18:11.214746Z", - "iopub.status.idle": "2023-07-26T05:18:11.217935Z", - "shell.execute_reply": "2023-07-26T05:18:11.217596Z" + "iopub.execute_input": "2023-08-06T17:35:54.168856Z", + "iopub.status.busy": "2023-08-06T17:35:54.168772Z", + "iopub.status.idle": "2023-08-06T17:35:54.171306Z", + "shell.execute_reply": "2023-08-06T17:35:54.171036Z" }, "lines_to_next_cell": 2 }, @@ -1642,7 +1642,7 @@ { "data": { "text/plain": [ - "0.711356743429736" + "0.7113567434297362" ] }, "execution_count": 31, @@ -1689,10 +1689,10 @@ "id": "345fb41e", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.220117Z", - "iopub.status.busy": "2023-07-26T05:18:11.219983Z", - "iopub.status.idle": "2023-07-26T05:18:11.222355Z", - "shell.execute_reply": "2023-07-26T05:18:11.221948Z" + "iopub.execute_input": "2023-08-06T17:35:54.172898Z", + "iopub.status.busy": "2023-08-06T17:35:54.172820Z", + "iopub.status.idle": "2023-08-06T17:35:54.174844Z", + "shell.execute_reply": "2023-08-06T17:35:54.174573Z" }, "lines_to_next_cell": 0 }, @@ -1718,10 +1718,10 @@ "id": "3a8c21a2", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.224388Z", - "iopub.status.busy": "2023-07-26T05:18:11.224258Z", - "iopub.status.idle": "2023-07-26T05:18:11.262343Z", - "shell.execute_reply": "2023-07-26T05:18:11.261799Z" + "iopub.execute_input": "2023-08-06T17:35:54.176279Z", + "iopub.status.busy": "2023-08-06T17:35:54.176201Z", + "iopub.status.idle": "2023-08-06T17:35:54.490075Z", + "shell.execute_reply": "2023-08-06T17:35:54.489602Z" }, "lines_to_next_cell": 0 }, @@ -1746,10 +1746,10 @@ "id": "e3e35b5d", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.265599Z", - "iopub.status.busy": "2023-07-26T05:18:11.265438Z", - "iopub.status.idle": "2023-07-26T05:18:11.268983Z", - "shell.execute_reply": "2023-07-26T05:18:11.268283Z" + "iopub.execute_input": "2023-08-06T17:35:54.492349Z", + "iopub.status.busy": "2023-08-06T17:35:54.492209Z", + "iopub.status.idle": "2023-08-06T17:35:54.495557Z", + "shell.execute_reply": "2023-08-06T17:35:54.495020Z" }, "lines_to_next_cell": 0 }, @@ -1757,9 +1757,9 @@ { "data": { "text/plain": [ - "array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0,\n", - " 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", - " 0, 0, 0, 0, 0, 0], dtype=int32)" + "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,\n", + " 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n", + " 1, 1, 1, 1, 1, 1], dtype=int32)" ] }, "execution_count": 34, @@ -1788,16 +1788,16 @@ "id": "d928650a", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.271491Z", - "iopub.status.busy": "2023-07-26T05:18:11.271353Z", - "iopub.status.idle": "2023-07-26T05:18:11.409914Z", - "shell.execute_reply": "2023-07-26T05:18:11.409365Z" + "iopub.execute_input": "2023-08-06T17:35:54.497396Z", + "iopub.status.busy": "2023-08-06T17:35:54.497311Z", + "iopub.status.idle": "2023-08-06T17:35:54.605692Z", + "shell.execute_reply": "2023-08-06T17:35:54.605294Z" } }, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -1835,17 +1835,17 @@ "id": "92e5175c", "metadata": { "execution": { - "iopub.execute_input": "2023-07-26T05:18:11.412487Z", - "iopub.status.busy": "2023-07-26T05:18:11.412250Z", - "iopub.status.idle": "2023-07-26T05:18:11.548124Z", - "shell.execute_reply": "2023-07-26T05:18:11.547642Z" + "iopub.execute_input": "2023-08-06T17:35:54.608086Z", + "iopub.status.busy": "2023-08-06T17:35:54.607746Z", + "iopub.status.idle": "2023-08-06T17:35:54.725343Z", + "shell.execute_reply": "2023-08-06T17:35:54.725007Z" }, "lines_to_next_cell": 0 }, "outputs": [ { "data": { - "image/png": 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", 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", 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AgglomerativeClustering(distance_threshold=0, linkage='complete',\n",
+       "
AgglomerativeClustering(distance_threshold=0, linkage='complete',\n",
        "                        n_clusters=None)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
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@@ -2004,10 +2004,10 @@
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-     "iopub.execute_input": "2023-07-26T05:18:11.580226Z",
-     "iopub.status.busy": "2023-07-26T05:18:11.580003Z",
-     "iopub.status.idle": "2023-07-26T05:18:11.583835Z",
-     "shell.execute_reply": "2023-07-26T05:18:11.583381Z"
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+     "shell.execute_reply": "2023-08-06T17:35:54.755609Z"
     }
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    "outputs": [],
@@ -2037,17 +2037,17 @@
    "id": "bf7a2408",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:11.586413Z",
-     "iopub.status.busy": "2023-07-26T05:18:11.586258Z",
-     "iopub.status.idle": "2023-07-26T05:18:11.591990Z",
-     "shell.execute_reply": "2023-07-26T05:18:11.591553Z"
+     "iopub.execute_input": "2023-08-06T17:35:54.758124Z",
+     "iopub.status.busy": "2023-08-06T17:35:54.757853Z",
+     "iopub.status.idle": "2023-08-06T17:35:54.763112Z",
+     "shell.execute_reply": "2023-08-06T17:35:54.762785Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "
AgglomerativeClustering(distance_threshold=0, linkage='single',\n",
+       "
AgglomerativeClustering(distance_threshold=0, linkage='single',\n",
        "                        metric='precomputed', n_clusters=None)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
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@@ -2097,10 +2097,10 @@
    "id": "a118c0ab",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:11.595666Z",
-     "iopub.status.busy": "2023-07-26T05:18:11.595400Z",
-     "iopub.status.idle": "2023-07-26T05:18:11.876074Z",
-     "shell.execute_reply": "2023-07-26T05:18:11.875555Z"
+     "iopub.execute_input": "2023-08-06T17:35:54.764945Z",
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     }
    },
    "outputs": [
@@ -2142,10 +2142,10 @@
    "id": "b1ff41c0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:11.878711Z",
-     "iopub.status.busy": "2023-07-26T05:18:11.878497Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.156685Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.156217Z"
+     "iopub.execute_input": "2023-08-06T17:35:54.998527Z",
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+     "iopub.status.idle": "2023-08-06T17:35:55.224328Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.224001Z"
     }
    },
    "outputs": [
@@ -2184,10 +2184,10 @@
    "id": "c2752a96",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.159239Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.159059Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.163542Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.163127Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.226138Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.226012Z",
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     }
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    "outputs": [
@@ -2226,10 +2226,10 @@
    "id": "1407f7a4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.165971Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.165813Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.170809Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.170332Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.231139Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.231047Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.234414Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.234103Z"
     }
    },
    "outputs": [
@@ -2312,10 +2312,10 @@
    "id": "2d74f224",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.173359Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.173198Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.457460Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.457026Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.236000Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.235892Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.466992Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.466654Z"
     }
    },
    "outputs": [
@@ -2367,10 +2367,10 @@
    "id": "b7f7da12",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.461207Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.460949Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.680696Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.680192Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.468711Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.468585Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.650076Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.649676Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2419,10 +2419,10 @@
    "id": "b94424fc",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.683099Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.682918Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.688821Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.688474Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.651855Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.651741Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.658795Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.658519Z"
     }
    },
    "outputs": [],
@@ -2452,10 +2452,10 @@
    "id": "cea54566",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.691075Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.690934Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.693705Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.693319Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.660436Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.660347Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.662725Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.662438Z"
     },
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    },
@@ -2489,10 +2489,10 @@
    "id": "4dac41bb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.695954Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.695815Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.700521Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.700074Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.664308Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.664169Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.668246Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.667892Z"
     },
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    },
@@ -2545,10 +2545,10 @@
    "id": "d8ebadd6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.702785Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.702646Z",
-     "iopub.status.idle": "2023-07-26T05:18:12.866311Z",
-     "shell.execute_reply": "2023-07-26T05:18:12.856469Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.669892Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.669796Z",
+     "iopub.status.idle": "2023-08-06T17:35:55.812837Z",
+     "shell.execute_reply": "2023-08-06T17:35:55.811884Z"
     }
    },
    "outputs": [],
@@ -2577,10 +2577,10 @@
    "id": "63b5efe3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:12.882679Z",
-     "iopub.status.busy": "2023-07-26T05:18:12.878318Z",
-     "iopub.status.idle": "2023-07-26T05:18:13.099177Z",
-     "shell.execute_reply": "2023-07-26T05:18:13.098712Z"
+     "iopub.execute_input": "2023-08-06T17:35:55.818431Z",
+     "iopub.status.busy": "2023-08-06T17:35:55.818044Z",
+     "iopub.status.idle": "2023-08-06T17:35:56.078668Z",
+     "shell.execute_reply": "2023-08-06T17:35:56.078379Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2647,10 +2647,10 @@
    "id": "e20c3cc1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:13.101683Z",
-     "iopub.status.busy": "2023-07-26T05:18:13.101534Z",
-     "iopub.status.idle": "2023-07-26T05:18:13.327522Z",
-     "shell.execute_reply": "2023-07-26T05:18:13.327041Z"
+     "iopub.execute_input": "2023-08-06T17:35:56.080337Z",
+     "iopub.status.busy": "2023-08-06T17:35:56.080250Z",
+     "iopub.status.idle": "2023-08-06T17:35:56.227591Z",
+     "shell.execute_reply": "2023-08-06T17:35:56.227252Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2720,10 +2720,10 @@
    "id": "622de805",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:13.330190Z",
-     "iopub.status.busy": "2023-07-26T05:18:13.330013Z",
-     "iopub.status.idle": "2023-07-26T05:18:13.332964Z",
-     "shell.execute_reply": "2023-07-26T05:18:13.332533Z"
+     "iopub.execute_input": "2023-08-06T17:35:56.229339Z",
+     "iopub.status.busy": "2023-08-06T17:35:56.229217Z",
+     "iopub.status.idle": "2023-08-06T17:35:56.231787Z",
+     "shell.execute_reply": "2023-08-06T17:35:56.231485Z"
     }
    },
    "outputs": [],
@@ -2758,10 +2758,10 @@
    "id": "54d40449",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:13.336193Z",
-     "iopub.status.busy": "2023-07-26T05:18:13.335972Z",
-     "iopub.status.idle": "2023-07-26T05:18:14.886877Z",
-     "shell.execute_reply": "2023-07-26T05:18:14.886190Z"
+     "iopub.execute_input": "2023-08-06T17:35:56.233590Z",
+     "iopub.status.busy": "2023-08-06T17:35:56.233477Z",
+     "iopub.status.idle": "2023-08-06T17:35:57.584097Z",
+     "shell.execute_reply": "2023-08-06T17:35:57.583812Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2811,10 +2811,10 @@
    "id": "dc80afc8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:14.891531Z",
-     "iopub.status.busy": "2023-07-26T05:18:14.890910Z",
-     "iopub.status.idle": "2023-07-26T05:18:14.903469Z",
-     "shell.execute_reply": "2023-07-26T05:18:14.903077Z"
+     "iopub.execute_input": "2023-08-06T17:35:57.585856Z",
+     "iopub.status.busy": "2023-08-06T17:35:57.585741Z",
+     "iopub.status.idle": "2023-08-06T17:35:57.597998Z",
+     "shell.execute_reply": "2023-08-06T17:35:57.597730Z"
     },
     "lines_to_next_cell": 2
    },
@@ -3005,10 +3005,10 @@
    "id": "40ff59f9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:14.905992Z",
-     "iopub.status.busy": "2023-07-26T05:18:14.905760Z",
-     "iopub.status.idle": "2023-07-26T05:18:15.399751Z",
-     "shell.execute_reply": "2023-07-26T05:18:15.399237Z"
+     "iopub.execute_input": "2023-08-06T17:35:57.599540Z",
+     "iopub.status.busy": "2023-08-06T17:35:57.599448Z",
+     "iopub.status.idle": "2023-08-06T17:35:58.032539Z",
+     "shell.execute_reply": "2023-08-06T17:35:58.032140Z"
     }
    },
    "outputs": [
@@ -3054,10 +3054,10 @@
    "id": "1587e83b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:15.401922Z",
-     "iopub.status.busy": "2023-07-26T05:18:15.401768Z",
-     "iopub.status.idle": "2023-07-26T05:18:17.931480Z",
-     "shell.execute_reply": "2023-07-26T05:18:17.924183Z"
+     "iopub.execute_input": "2023-08-06T17:35:58.034342Z",
+     "iopub.status.busy": "2023-08-06T17:35:58.034213Z",
+     "iopub.status.idle": "2023-08-06T17:35:58.251720Z",
+     "shell.execute_reply": "2023-08-06T17:35:58.251045Z"
     }
    },
    "outputs": [
@@ -3098,30 +3098,30 @@
        "  \n",
        "    \n",
        "      0\n",
-       "      28\n",
-       "      3\n",
+       "      1\n",
+       "      20\n",
+       "      10\n",
        "      9\n",
-       "      0\n",
        "    \n",
        "    \n",
        "      1\n",
-       "      7\n",
        "      0\n",
+       "      7\n",
        "      0\n",
        "      0\n",
        "    \n",
        "    \n",
        "      2\n",
-       "      0\n",
-       "      0\n",
-       "      0\n",
        "      8\n",
+       "      0\n",
+       "      0\n",
+       "      0\n",
        "    \n",
        "    \n",
        "      3\n",
        "      0\n",
-       "      9\n",
        "      0\n",
+       "      9\n",
        "      0\n",
        "    \n",
        "  \n",
@@ -3129,12 +3129,12 @@
        "
"
       ],
       "text/plain": [
-       "K-means   0  1  2  3\n",
-       "HClust              \n",
-       "0        28  3  9  0\n",
-       "1         7  0  0  0\n",
-       "2         0  0  0  8\n",
-       "3         0  9  0  0"
+       "K-means  0   1   2  3\n",
+       "HClust               \n",
+       "0        1  20  10  9\n",
+       "1        0   7   0  0\n",
+       "2        8   0   0  0\n",
+       "3        0   0   9  0"
       ]
      },
      "execution_count": 57,
@@ -3179,10 +3179,10 @@
    "id": "b09ceeab",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:18:17.955945Z",
-     "iopub.status.busy": "2023-07-26T05:18:17.954718Z",
-     "iopub.status.idle": "2023-07-26T05:18:18.488264Z",
-     "shell.execute_reply": "2023-07-26T05:18:18.487809Z"
+     "iopub.execute_input": "2023-08-06T17:35:58.255255Z",
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@@ -3405,7 +3405,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.4"
   }
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  "nbformat": 4,
diff --git a/Ch13-multiple-lab.ipynb b/Ch13-multiple-lab.ipynb
index 65fb5bb..83fad7d 100644
--- a/Ch13-multiple-lab.ipynb
+++ b/Ch13-multiple-lab.ipynb
@@ -26,10 +26,10 @@
    "id": "1f928b2d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T10:52:21.791802Z",
-     "iopub.status.busy": "2023-07-26T10:52:21.791660Z",
-     "iopub.status.idle": "2023-07-26T10:52:23.360588Z",
-     "shell.execute_reply": "2023-07-26T10:52:23.359991Z"
+     "iopub.execute_input": "2023-08-06T17:36:00.152825Z",
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+     "shell.execute_reply": "2023-08-06T17:36:01.253710Z"
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    "outputs": [],
@@ -56,10 +56,10 @@
    "id": "eb4b32aa",
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-     "iopub.execute_input": "2023-07-26T10:52:23.363356Z",
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-     "shell.execute_reply": "2023-07-26T10:52:23.365438Z"
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@@ -95,10 +95,10 @@
    "id": "e12ac0cd",
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-     "shell.execute_reply": "2023-07-26T10:52:23.370779Z"
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+     "shell.execute_reply": "2023-08-06T17:36:01.262174Z"
     }
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    "outputs": [],
@@ -125,10 +125,10 @@
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    "outputs": [
@@ -172,10 +172,10 @@
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@@ -208,10 +208,10 @@
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@@ -308,10 +308,10 @@
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@@ -420,10 +420,10 @@
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@@ -476,10 +476,10 @@
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@@ -544,10 +544,10 @@
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@@ -583,10 +583,10 @@
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@@ -625,10 +625,10 @@
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@@ -664,10 +664,10 @@
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@@ -708,10 +708,10 @@
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@@ -760,10 +760,10 @@
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@@ -820,10 +820,10 @@
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@@ -861,10 +861,10 @@
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@@ -890,10 +890,10 @@
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@@ -935,10 +935,10 @@
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@@ -979,10 +979,10 @@
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@@ -1029,10 +1029,10 @@
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@@ -1063,10 +1063,10 @@
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@@ -1113,10 +1113,10 @@
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@@ -1164,10 +1164,10 @@
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@@ -1217,10 +1217,10 @@
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@@ -1268,10 +1268,10 @@
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-     "shell.execute_reply": "2023-07-26T10:52:26.458144Z"
+     "iopub.execute_input": "2023-08-06T17:36:05.381564Z",
+     "iopub.status.busy": "2023-08-06T17:36:05.381435Z",
+     "iopub.status.idle": "2023-08-06T17:36:05.597223Z",
+     "shell.execute_reply": "2023-08-06T17:36:05.596880Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1328,10 +1328,10 @@
    "id": "3b7392cb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T10:52:26.461754Z",
-     "iopub.status.busy": "2023-07-26T10:52:26.461349Z",
-     "iopub.status.idle": "2023-07-26T12:21:43.650925Z",
-     "shell.execute_reply": "2023-07-26T12:21:43.650584Z"
+     "iopub.execute_input": "2023-08-06T17:36:05.599334Z",
+     "iopub.status.busy": "2023-08-06T17:36:05.599205Z",
+     "iopub.status.idle": "2023-08-06T17:40:01.929123Z",
+     "shell.execute_reply": "2023-08-06T17:40:01.928341Z"
     }
    },
    "outputs": [],
@@ -1374,10 +1374,10 @@
    "id": "cac15616",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T12:21:43.653105Z",
-     "iopub.status.busy": "2023-07-26T12:21:43.652856Z",
-     "iopub.status.idle": "2023-07-26T12:21:43.895651Z",
-     "shell.execute_reply": "2023-07-26T12:21:43.895292Z"
+     "iopub.execute_input": "2023-08-06T17:40:01.931393Z",
+     "iopub.status.busy": "2023-08-06T17:40:01.931250Z",
+     "iopub.status.idle": "2023-08-06T17:40:02.050525Z",
+     "shell.execute_reply": "2023-08-06T17:40:02.050215Z"
     }
    },
    "outputs": [],
@@ -1415,10 +1415,10 @@
    "id": "9661eb10",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T12:21:43.897943Z",
-     "iopub.status.busy": "2023-07-26T12:21:43.897797Z",
-     "iopub.status.idle": "2023-07-26T12:21:43.901002Z",
-     "shell.execute_reply": "2023-07-26T12:21:43.900637Z"
+     "iopub.execute_input": "2023-08-06T17:40:02.052324Z",
+     "iopub.status.busy": "2023-08-06T17:40:02.052224Z",
+     "iopub.status.idle": "2023-08-06T17:40:02.054968Z",
+     "shell.execute_reply": "2023-08-06T17:40:02.054729Z"
     }
    },
    "outputs": [
@@ -1470,10 +1470,10 @@
    "id": "18ad4900",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T12:21:43.902778Z",
-     "iopub.status.busy": "2023-07-26T12:21:43.902684Z",
-     "iopub.status.idle": "2023-07-26T12:21:43.905535Z",
-     "shell.execute_reply": "2023-07-26T12:21:43.905228Z"
+     "iopub.execute_input": "2023-08-06T17:40:02.056480Z",
+     "iopub.status.busy": "2023-08-06T17:40:02.056382Z",
+     "iopub.status.idle": "2023-08-06T17:40:02.058766Z",
+     "shell.execute_reply": "2023-08-06T17:40:02.058503Z"
     }
    },
    "outputs": [
@@ -1538,10 +1538,10 @@
    "id": "28c276b6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T12:21:43.907278Z",
-     "iopub.status.busy": "2023-07-26T12:21:43.907150Z",
-     "iopub.status.idle": "2023-07-26T12:21:43.988689Z",
-     "shell.execute_reply": "2023-07-26T12:21:43.988352Z"
+     "iopub.execute_input": "2023-08-06T17:40:02.060234Z",
+     "iopub.status.busy": "2023-08-06T17:40:02.060135Z",
+     "iopub.status.idle": "2023-08-06T17:40:02.135583Z",
+     "shell.execute_reply": "2023-08-06T17:40:02.135228Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1589,7 +1589,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/Ch2-statlearn-lab.ipynb b/Ch2-statlearn-lab.ipynb
index d0344cd..d4edc10 100644
--- a/Ch2-statlearn-lab.ipynb
+++ b/Ch2-statlearn-lab.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "46456e09",
+   "id": "4a4000ea",
    "metadata": {},
    "source": [
     "\n",
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e9222139",
+   "id": "ca503bf1",
    "metadata": {},
    "source": [
     "## Getting Started"
@@ -22,7 +22,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a84726ab",
+   "id": "4d90d49a",
    "metadata": {},
    "source": [
     "To run the labs in this book, you will need two things:\n",
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f922cc9e",
+   "id": "c05e9a74",
    "metadata": {},
    "source": [
     "You can download and install  `Python3`   by following the instructions available at [anaconda.com](http://anaconda.com). "
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "baaeada6",
+   "id": "a4fa6a12",
    "metadata": {},
    "source": [
     " There are a number of ways to get access to `Jupyter`. Here are just a few:\n",
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7a44fbd9",
+   "id": "fb245ea1",
    "metadata": {},
    "source": [
     "## Basic Commands\n"
@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3831ff0d",
+   "id": "df72fe8e",
    "metadata": {},
    "source": [
     "In this lab, we will introduce some simple `Python` commands. \n",
@@ -83,7 +83,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b5460488",
+   "id": "713233e6",
    "metadata": {},
    "source": [
     "Like most programming languages, `Python` uses *functions*\n",
@@ -99,13 +99,13 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "88d0bfff",
+   "id": "3e6aae64",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.653253Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.653107Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.659825Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.659469Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.285475Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.285130Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.294270Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.293851Z"
     }
    },
    "outputs": [
@@ -123,7 +123,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9c07629a",
+   "id": "790e89ef",
    "metadata": {},
    "source": [
     " The following command will provide information about the `print()` function."
@@ -132,13 +132,13 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "ebe7aca8",
+   "id": "086066fd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.662377Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.662207Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.664797Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.664422Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.296567Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.296382Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.324226Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.323953Z"
     }
    },
    "outputs": [],
@@ -148,7 +148,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b0c41d18",
+   "id": "1519b474",
    "metadata": {},
    "source": [
     "Adding two integers in `Python` is pretty intuitive."
@@ -157,13 +157,13 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "df2f8168",
+   "id": "cb86e827",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.666990Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.666828Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.670697Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.670233Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.325751Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.325655Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.328625Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.328385Z"
     }
    },
    "outputs": [
@@ -184,7 +184,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7e7b4195",
+   "id": "995ac4a8",
    "metadata": {},
    "source": [
     "In `Python`, textual data is handled using\n",
@@ -197,13 +197,13 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "4cc5c2c1",
+   "id": "f4d45d80",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.673136Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.672979Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.675685Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.675286Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.330134Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.330050Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.332103Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.331834Z"
     }
    },
    "outputs": [
@@ -224,7 +224,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cfda314a",
+   "id": "54a86535",
    "metadata": {},
    "source": [
     " A string is actually a type of *sequence*: this is a generic term for an ordered list. \n",
@@ -234,7 +234,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "764ca7ea",
+   "id": "f2cd64af",
    "metadata": {},
    "source": [
     "The following command instructs `Python` to join together\n",
@@ -246,13 +246,13 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "e5d81180",
+   "id": "e386aff9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.677943Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.677800Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.680585Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.680100Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.333600Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.333503Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.335528Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.335290Z"
     }
    },
    "outputs": [
@@ -274,7 +274,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a2e75dce",
+   "id": "185fdcfa",
    "metadata": {},
    "source": [
     "Note that we used the brackets\n",
@@ -287,13 +287,13 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "425a714c",
+   "id": "f81b1212",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.682740Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.682602Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.685374Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.684966Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.336973Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.336873Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.338920Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.338661Z"
     }
    },
    "outputs": [
@@ -315,7 +315,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "245f069e",
+   "id": "f421a679",
    "metadata": {},
    "source": [
     "The result may appear slightly counterintuitive: why did `Python` not add the entries of the lists\n",
@@ -327,20 +327,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "071caddd",
+   "id": "911db9e2",
    "metadata": {},
    "source": [
     "This example reflects the fact that \n",
     " `Python` is a general-purpose programming language. Much of `Python`'s  data-specific\n",
     "functionality comes from other packages, notably `numpy`\n",
     "and `pandas`. \n",
-    "In the next section, we will introduce the  `numpy` package. More information about `numpy` can be found  at \n",
-    "[docs.scipy.org/doc/numpy/user/quickstart.html](https://docs.scipy.org/doc/numpy/user/quickstart.html).\n"
+    "In the next section, we will introduce the  `numpy` package. \n",
+    "See [docs.scipy.org/doc/numpy/user/quickstart.html](https://docs.scipy.org/doc/numpy/user/quickstart.html) for more information about `numpy`.\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "25581a8e",
+   "id": "2045f04d",
    "metadata": {},
    "source": [
     "## Introduction to Numerical Python\n",
@@ -352,7 +352,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "851a40d6",
+   "id": "b4ef08ea",
    "metadata": {},
    "source": [
     "  To access `numpy`, we must first `import` it."
@@ -361,13 +361,13 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "2f88669a",
+   "id": "13739a14",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.688017Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.687702Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.902613Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.901721Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.340405Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.340311Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.397337Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.396647Z"
     },
     "lines_to_next_cell": 0
    },
@@ -378,7 +378,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5bdc55d1",
+   "id": "587207d9",
    "metadata": {},
    "source": [
     "In the previous line, we named the `numpy` *module* `np`; an abbreviation for easier referencing."
@@ -386,7 +386,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7b2cbe8b",
+   "id": "c485aeb9",
    "metadata": {},
    "source": [
     "In `numpy`, an *array* is  a generic term for a multidimensional\n",
@@ -397,13 +397,13 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "e8ec382a",
+   "id": "f3f62d0a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.908393Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.907922Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.914563Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.912356Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.401823Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.401514Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.406194Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.404998Z"
     },
     "lines_to_next_cell": 0
    },
@@ -415,7 +415,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3a5ce193",
+   "id": "d5e7e5e3",
    "metadata": {},
    "source": [
     "Note that if you forgot to run the `import numpy as np` command earlier, then\n",
@@ -426,7 +426,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b21e6ebd",
+   "id": "5ba313c6",
    "metadata": {},
    "source": [
     "Since `x` and `y` have been defined using `np.array()`, we get a sensible result when we add them together. Compare this to our results in the previous section,\n",
@@ -436,13 +436,13 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "04de39ad",
+   "id": "3cff111f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.919758Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.919275Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.929618Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.928417Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.410267Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.410044Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.416300Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.415133Z"
     },
     "lines_to_next_cell": 0
    },
@@ -464,7 +464,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "06a14452",
+   "id": "96db430f",
    "metadata": {},
    "source": [
     "    \n",
@@ -473,7 +473,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "33df3775",
+   "id": "801647e7",
    "metadata": {},
    "source": [
     "In `numpy`, matrices are typically represented as two-dimensional arrays, and vectors as one-dimensional arrays. {While it is also possible to create matrices using  `np.matrix()`, we will use `np.array()` throughout the labs in this book.}\n",
@@ -483,13 +483,13 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "fee5d798",
+   "id": "30d6c7f8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.934509Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.934172Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.941331Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.939888Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.420244Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.419921Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.426497Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.425722Z"
     },
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    },
@@ -513,7 +513,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c04d19a8",
+   "id": "5df2b6c3",
    "metadata": {},
    "source": [
     "    \n",
@@ -522,7 +522,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "86de84a5",
+   "id": "d7804f5e",
    "metadata": {},
    "source": [
     "The object `x` has several \n",
@@ -534,13 +534,13 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "5871ca00",
+   "id": "42d49be4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.946610Z",
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-     "iopub.status.idle": "2023-07-26T05:29:13.952982Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.951422Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.430547Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.430144Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.436651Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.435793Z"
     }
    },
    "outputs": [
@@ -561,7 +561,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "71a44f8e",
+   "id": "765e1496",
    "metadata": {},
    "source": [
     "The output indicates that `x` is a two-dimensional array.  \n",
@@ -572,13 +572,13 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "5a32759c",
+   "id": "de32b275",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.958221Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.957674Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.965373Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.964551Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.440754Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.440389Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.447906Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.447260Z"
     },
     "lines_to_next_cell": 0
    },
@@ -600,7 +600,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e770da51",
+   "id": "044bf011",
    "metadata": {},
    "source": [
     "Why is `x` comprised of integers? This is because we created `x` by passing in exclusively integers to the `np.array()` function.\n",
@@ -612,13 +612,13 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "55f01b16",
+   "id": "528c3fa0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.970795Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.970020Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.977698Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.976971Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.451815Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.451466Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.459974Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.459261Z"
     },
     "lines_to_next_cell": 2
    },
@@ -640,7 +640,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4595300f",
+   "id": "053da117",
    "metadata": {},
    "source": [
     "Typing `fun?` will cause `Python` to display \n",
@@ -651,13 +651,13 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "2a9de618",
+   "id": "fbf8763b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.983003Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.982433Z",
-     "iopub.status.idle": "2023-07-26T05:29:13.987748Z",
-     "shell.execute_reply": "2023-07-26T05:29:13.986808Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.463710Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.463173Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.468333Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.467532Z"
     },
     "lines_to_next_cell": 0
    },
@@ -668,7 +668,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9640f3fe",
+   "id": "0df45f3d",
    "metadata": {},
    "source": [
     "This documentation indicates that we could create a floating point array by passing a `dtype` argument into `np.array()`."
@@ -677,13 +677,13 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "33e3e6ea",
+   "id": "482d0c05",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:13.997637Z",
-     "iopub.status.busy": "2023-07-26T05:29:13.996561Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.002488Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.001948Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.472515Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.472028Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.479510Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.478563Z"
     },
     "lines_to_next_cell": 2
    },
@@ -705,7 +705,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fbf59c0e",
+   "id": "757c10a0",
    "metadata": {},
    "source": [
     "The array `x` is two-dimensional. We can find out the number of rows and columns by looking\n",
@@ -715,13 +715,13 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "623f8434",
+   "id": "192cdf26",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.004972Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.004832Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.007701Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.007253Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.483171Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.482882Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.489459Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.488833Z"
     },
     "lines_to_next_cell": 2
    },
@@ -743,7 +743,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "81f0bbae",
+   "id": "b3d091f4",
    "metadata": {},
    "source": [
     "A *method* is a function that is associated with an\n",
@@ -758,13 +758,13 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "235738a7",
+   "id": "4420b967",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.010160Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.009950Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.013139Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.012702Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.493523Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.493057Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.499969Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.499303Z"
     },
     "lines_to_next_cell": 0
    },
@@ -787,7 +787,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "72373ccf",
+   "id": "ca0ff297",
    "metadata": {},
    "source": [
     "We could also sum the elements of `x` by passing in `x` as an argument to the `np.sum()` function. "
@@ -796,13 +796,13 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "7f3494e1",
+   "id": "5af5e20f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.015464Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.015347Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.018540Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.017992Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.503658Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.503289Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.510540Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.509832Z"
     },
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    },
@@ -825,7 +825,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "69967e23",
+   "id": "355ad58f",
    "metadata": {},
    "source": [
     " As another example, the\n",
@@ -842,13 +842,13 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "0ca8f936",
+   "id": "77a0df31",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.020924Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.020756Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.023635Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.023118Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.514507Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.514084Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.520423Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.519754Z"
     }
    },
    "outputs": [
@@ -873,7 +873,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c1e36ab",
+   "id": "e68cddfa",
    "metadata": {},
    "source": [
     "The previous output reveals that `numpy` arrays are specified as a sequence\n",
@@ -882,7 +882,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "45263db2",
+   "id": "4b16c07d",
    "metadata": {},
    "source": [
     "`Python` (and hence `numpy`) uses 0-based\n",
@@ -893,13 +893,13 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "23fba624",
+   "id": "c57ce2ca",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.026491Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.026156Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.029404Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.028872Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.524768Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.524519Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.537593Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.536180Z"
     },
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    },
@@ -921,7 +921,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "26f1717c",
+   "id": "9a4feee5",
    "metadata": {},
    "source": [
     "Similarly, `x_reshape[1,2]` yields the element in the second row and the third column \n",
@@ -931,13 +931,13 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "1a1df926",
+   "id": "ea55b034",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.031676Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.031560Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.034395Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.033993Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.541338Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.541124Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.551129Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.550354Z"
     },
     "lines_to_next_cell": 0
    },
@@ -959,7 +959,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c6d6d359",
+   "id": "7a3c27dd",
    "metadata": {},
    "source": [
     "Similarly, `x[2]` yields the\n",
@@ -972,13 +972,13 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "4bfcc1e1",
+   "id": "b897a965",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.036755Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.036603Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.039645Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.039150Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.555575Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.555273Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.561872Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.560597Z"
     }
    },
    "outputs": [
@@ -1009,7 +1009,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "10ff8c21",
+   "id": "77ab8534",
    "metadata": {},
    "source": [
     "Modifying `x_reshape` also modified `x` because the two objects occupy the same space in memory.\n",
@@ -1020,7 +1020,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ff267ecb",
+   "id": "8d5214bc",
    "metadata": {},
    "source": [
     "We just saw that we can modify an element of an array. Can we also modify a tuple? It turns out that we cannot --- and trying to do so introduces\n",
@@ -1030,13 +1030,13 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "973c562a",
+   "id": "1de2f886",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.042240Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.042111Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.226949Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.226329Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.573227Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.572937Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.703228Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.702951Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1060,7 +1060,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "56393fe3",
+   "id": "5f8a5095",
    "metadata": {},
    "source": [
     "We now briefly mention some attributes of arrays that will come in handy. An array's `shape` attribute contains its dimension; this is always a tuple.\n",
@@ -1070,13 +1070,13 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "56b5c382",
+   "id": "634a18d8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.229928Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.229597Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.233213Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.232504Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.704897Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.704794Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.707079Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.706824Z"
     }
    },
    "outputs": [
@@ -1101,7 +1101,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22408350",
+   "id": "1db9f878",
    "metadata": {},
    "source": [
     "Notice that the three individual outputs `(2,3)`, `2`, and `array([[5, 4],[2, 5], [3,6]])` are themselves output as a tuple. \n",
@@ -1114,13 +1114,13 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "2e624622",
+   "id": "38563574",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.235702Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.235564Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.238916Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.238262Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.708463Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.708366Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.710497Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.710237Z"
     }
    },
    "outputs": [
@@ -1142,7 +1142,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6c3e074d",
+   "id": "cdee1904",
    "metadata": {},
    "source": [
     "We can also square the elements:"
@@ -1151,13 +1151,13 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "6f45bd25",
+   "id": "6d7eb044",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.241171Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.241044Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.244021Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.243599Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.711918Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.711824Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.713705Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.713469Z"
     }
    },
    "outputs": [
@@ -1178,7 +1178,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "481ca03c",
+   "id": "7322f04a",
    "metadata": {},
    "source": [
     "We can compute the square roots using the same notation, raising to the power of $1/2$ instead of 2."
@@ -1187,13 +1187,13 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "6980f628",
+   "id": "dcf49c32",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.246394Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.246080Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.249174Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.248827Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.715100Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.715015Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.717032Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.716796Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1216,7 +1216,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc357745",
+   "id": "a4ccea4f",
    "metadata": {},
    "source": [
     "Throughout this book, we will often want to generate random data. \n",
@@ -1234,29 +1234,29 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "89e32100",
+   "id": "dec2f36f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.251585Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.251451Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.254814Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.254443Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.718403Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.718308Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.720577Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.720323Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([ 0.85533175, -0.05576735, -0.51395487,  0.48888859, -1.48893364,\n",
-       "        0.26407493, -0.74669908,  1.01666253, -1.94048948, -1.78664297,\n",
-       "       -0.87797144,  0.62042405,  0.13462126,  0.09661092,  0.53420093,\n",
-       "       -0.36120885, -0.68012567, -2.26865778,  1.25520664,  0.51353373,\n",
-       "       -0.24985298, -0.41566987,  1.2875835 ,  0.38602031,  0.32079709,\n",
-       "       -0.26039978, -0.46997695, -0.34450981, -0.68854144,  0.90905649,\n",
-       "       -0.39245431, -0.22266431, -0.24441341,  0.47310767,  0.08102761,\n",
-       "        1.12966294,  0.50395953,  0.63130366,  0.50263731,  1.13393742,\n",
-       "        1.16885142, -0.89388268, -0.25282564,  0.32889275,  0.00619299,\n",
-       "        1.36017422,  0.10199394, -2.33500839,  1.12284979,  1.06710912])"
+       "array([-0.98985585,  0.78794313, -1.59659373,  1.11006429, -0.19527724,\n",
+       "       -1.49222447, -1.63557764,  2.0998599 , -1.05798913,  0.22654563,\n",
+       "       -2.48042733,  1.53705085,  1.17455819,  0.19093254, -0.2819633 ,\n",
+       "       -1.11688619, -1.58430027, -0.58351755,  0.52620187, -0.14465477,\n",
+       "        0.84609267, -0.06187834, -0.37385525,  1.27932599,  0.85681759,\n",
+       "       -0.11171155,  0.30777588, -1.08741173,  0.60531981, -0.48213946,\n",
+       "       -0.70477606,  0.34160113, -0.44446051, -0.67950574,  1.02276341,\n",
+       "        2.18072377,  0.46699258,  0.28226576, -0.26951424,  2.06603321,\n",
+       "       -0.0803351 ,  1.04171103, -0.54035202, -1.89733049, -1.86300407,\n",
+       "       -0.06721318,  0.4822852 , -0.29686638, -0.19377943,  2.03320645])"
       ]
      },
      "execution_count": 28,
@@ -1271,7 +1271,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "80939b41",
+   "id": "9c60001d",
    "metadata": {},
    "source": [
     "We create an array `y` by adding an independent $N(50,1)$ random variable to each element of `x`."
@@ -1280,13 +1280,13 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "e3428155",
+   "id": "f535fba4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.257670Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.257502Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.259844Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.259473Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.721992Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.721881Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.723589Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.723344Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1297,7 +1297,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "17f93000",
+   "id": "b267be24",
    "metadata": {},
    "source": [
     "The `np.corrcoef()` function computes the correlation matrix between `x` and `y`. The off-diagonal elements give the \n",
@@ -1307,21 +1307,21 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "df70172e",
+   "id": "faf3be25",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.262323Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.262139Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.266530Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.266141Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.724943Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.724855Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.727100Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.726847Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "array([[1.        , 0.58428739],\n",
-       "       [0.58428739, 1.        ]])"
+       "array([[1.        , 0.78790794],\n",
+       "       [0.78790794, 1.        ]])"
       ]
      },
      "execution_count": 30,
@@ -1335,7 +1335,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8fb44ec4",
+   "id": "c6d0e0ce",
    "metadata": {},
    "source": [
     "If you're following along in your own `Jupyter` notebook, then you probably noticed that you got a different set of results when you ran the past few \n",
@@ -1347,13 +1347,13 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "1d996956",
+   "id": "b6a756e0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.269539Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.269386Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.272569Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.271780Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.728472Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.728385Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.730292Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.730062Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1362,8 +1362,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[-3.0147683  -3.89425181]\n",
-      "[-0.22659461  1.61255642]\n"
+      "[3.08077237 4.8023279 ]\n",
+      "[-1.55255532  6.09934933]\n"
      ]
     }
    ],
@@ -1374,7 +1374,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "477c992d",
+   "id": "a1071413",
    "metadata": {},
    "source": [
     "    "
@@ -1382,7 +1382,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "988ca34a",
+   "id": "31d9911e",
    "metadata": {},
    "source": [
     "In order to ensure that our code provides exactly the same results\n",
@@ -1398,13 +1398,13 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "37b3a30b",
+   "id": "921b634a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.275409Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.275284Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.279259Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.278925Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.731733Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.731639Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.733796Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.733577Z"
     }
    },
    "outputs": [
@@ -1426,7 +1426,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "039e7f65",
+   "id": "7a4da703",
    "metadata": {},
    "source": [
     "Throughout the labs in this book, we use `np.random.default_rng()`  whenever we\n",
@@ -1444,13 +1444,13 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "b4f99e0e",
+   "id": "fe28973e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.282826Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.282508Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.285616Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.285268Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.735204Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.735110Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.737316Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.737055Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1474,7 +1474,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d3d0e0fb",
+   "id": "b6092d9c",
    "metadata": {},
    "source": [
     "    \n"
@@ -1483,13 +1483,13 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "dbd70319",
+   "id": "04c26742",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.287760Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.287646Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.290801Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.290395Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.738692Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.738597Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.740858Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.740608Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1511,7 +1511,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ba51f245",
+   "id": "b9212f82",
    "metadata": {},
    "source": [
     "Notice that by default `np.var()` divides by the sample size $n$ rather\n",
@@ -1521,13 +1521,13 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "id": "bf281844",
+   "id": "e35cdcbf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.292985Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.292843Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.295775Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.295412Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.742198Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.742113Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.744175Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.743929Z"
     }
    },
    "outputs": [
@@ -1548,7 +1548,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "877ca8e0",
+   "id": "41eb4c38",
    "metadata": {},
    "source": [
     "The `np.mean()`,  `np.var()`, and `np.std()` functions can also be applied to the rows and columns of a matrix. \n",
@@ -1558,13 +1558,13 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "id": "f751b1dd",
+   "id": "fbd49766",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.297946Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.297809Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.300890Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.300481Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.745532Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.745443Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.747554Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.747310Z"
     }
    },
    "outputs": [
@@ -1595,7 +1595,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f9028e1a",
+   "id": "5520aeae",
    "metadata": {},
    "source": [
     "Since arrays are row-major ordered, the first axis, i.e. `axis=0`, refers to its rows. We pass this argument into the `mean()` method for the object `X`. "
@@ -1604,13 +1604,13 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "id": "cbf92de5",
+   "id": "f5865859",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.303121Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.303004Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.306153Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.305697Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.748912Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.748822Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.750823Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.750599Z"
     }
    },
    "outputs": [
@@ -1631,7 +1631,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "009195d4",
+   "id": "8aedc41d",
    "metadata": {},
    "source": [
     "The following yields the same result."
@@ -1640,13 +1640,13 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "id": "efacc213",
+   "id": "e27b30bf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.308317Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.308171Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.311023Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.310704Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.752212Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.752121Z",
+     "iopub.status.idle": "2023-08-06T17:44:43.754183Z",
+     "shell.execute_reply": "2023-08-06T17:44:43.753947Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1668,7 +1668,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b42d9c6",
+   "id": "4ee7f516",
    "metadata": {},
    "source": [
     "    "
@@ -1676,7 +1676,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e33fa3fc",
+   "id": "80ab3209",
    "metadata": {},
    "source": [
     "## Graphics\n",
@@ -1710,13 +1710,13 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "id": "637fb67d",
+   "id": "fed2376c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.313130Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.312981Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.818758Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.818230Z"
+     "iopub.execute_input": "2023-08-06T17:44:43.755592Z",
+     "iopub.status.busy": "2023-08-06T17:44:43.755504Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.060228Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.059891Z"
     }
    },
    "outputs": [
@@ -1741,7 +1741,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ca04f15f",
+   "id": "9b697b2a",
    "metadata": {},
    "source": [
     "We pause here to note that we have *unpacked* the tuple of length two returned by `subplots()` into the two distinct\n",
@@ -1752,13 +1752,13 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "id": "109d681d",
+   "id": "228ee04d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.821437Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.821210Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.906268Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.905878Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.062068Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.061933Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.133359Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.133077Z"
     }
    },
    "outputs": [
@@ -1781,7 +1781,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5509508c",
+   "id": "e040ba84",
    "metadata": {},
    "source": [
     "We see that our earlier cell produced a line plot, which is the default. To create a scatterplot, we provide an additional argument to `ax.plot()`, indicating that circles should be displayed."
@@ -1790,13 +1790,13 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "id": "e905982c",
+   "id": "e1dc79d2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.908936Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.908699Z",
-     "iopub.status.idle": "2023-07-26T05:29:14.995469Z",
-     "shell.execute_reply": "2023-07-26T05:29:14.994686Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.135074Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.134956Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.210381Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.210084Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1819,7 +1819,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42166016",
+   "id": "960d0ceb",
    "metadata": {},
    "source": [
     "Different values\n",
@@ -1829,7 +1829,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a99dac78",
+   "id": "833d6751",
    "metadata": {},
    "source": [
     "As an alternative, we could use the  `ax.scatter()` function to create a scatterplot."
@@ -1838,13 +1838,13 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "id": "27133a4e",
+   "id": "d6e6bf34",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:14.997995Z",
-     "iopub.status.busy": "2023-07-26T05:29:14.997801Z",
-     "iopub.status.idle": "2023-07-26T05:29:15.089963Z",
-     "shell.execute_reply": "2023-07-26T05:29:15.089604Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.212226Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.212111Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.290879Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.290584Z"
     }
    },
    "outputs": [
@@ -1866,7 +1866,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "000c125e",
+   "id": "ff56b51f",
    "metadata": {},
    "source": [
     "Notice that in the code blocks above, we have ended\n",
@@ -1878,13 +1878,13 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "id": "ef41f90d",
+   "id": "9c1ea81c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:15.092622Z",
-     "iopub.status.busy": "2023-07-26T05:29:15.092487Z",
-     "iopub.status.idle": "2023-07-26T05:29:15.212584Z",
-     "shell.execute_reply": "2023-07-26T05:29:15.211918Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.292652Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.292524Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.371306Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.371033Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1892,7 +1892,7 @@
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
      "execution_count": 43,
@@ -1917,7 +1917,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "014f66e5",
+   "id": "abdc9ceb",
    "metadata": {},
    "source": [
     "In what follows, we will use\n",
@@ -1930,7 +1930,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98a1db4a",
+   "id": "4b9491f5",
    "metadata": {},
    "source": [
     "To label our plot, we  make use of the `set_xlabel()`,  `set_ylabel()`, and  `set_title()` methods\n",
@@ -1941,13 +1941,13 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "id": "16a9cb99",
+   "id": "e6217bc8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:15.215419Z",
-     "iopub.status.busy": "2023-07-26T05:29:15.215027Z",
-     "iopub.status.idle": "2023-07-26T05:29:15.330192Z",
-     "shell.execute_reply": "2023-07-26T05:29:15.328644Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.373100Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.372978Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.469578Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.469292Z"
     }
    },
    "outputs": [
@@ -1972,7 +1972,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7f0af2d9",
+   "id": "e8228a39",
    "metadata": {},
    "source": [
     " Having access to the figure object `fig` itself means that we can go in and change some aspects and then redisplay it. Here, we change\n",
@@ -1982,13 +1982,13 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "id": "6707420e",
+   "id": "2feef77c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:15.334119Z",
-     "iopub.status.busy": "2023-07-26T05:29:15.333963Z",
-     "iopub.status.idle": "2023-07-26T05:29:15.405814Z",
-     "shell.execute_reply": "2023-07-26T05:29:15.405400Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.471293Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.471177Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.533248Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.532956Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2012,7 +2012,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4b70cd2e",
+   "id": "d22f3886",
    "metadata": {},
    "source": [
     " "
@@ -2020,7 +2020,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3cf4ed3f",
+   "id": "e9187ea8",
    "metadata": {},
    "source": [
     "Occasionally we will want to create several plots within a figure. This can be\n",
@@ -2036,13 +2036,13 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "id": "6c78ef8b",
+   "id": "24c9bd3c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:15.408333Z",
-     "iopub.status.busy": "2023-07-26T05:29:15.408192Z",
-     "iopub.status.idle": "2023-07-26T05:29:15.732292Z",
-     "shell.execute_reply": "2023-07-26T05:29:15.731605Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.534878Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.534763Z",
+     "iopub.status.idle": "2023-08-06T17:44:44.819697Z",
+     "shell.execute_reply": "2023-08-06T17:44:44.819421Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2066,7 +2066,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "40d89b7c",
+   "id": "7c6bdba5",
    "metadata": {},
    "source": [
     "We now produce a scatter plot with `'o'` in the second column of the first row and\n",
@@ -2076,13 +2076,13 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "id": "a18402fb",
+   "id": "dbe7d87c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:15.734889Z",
-     "iopub.status.busy": "2023-07-26T05:29:15.734697Z",
-     "iopub.status.idle": "2023-07-26T05:29:15.959530Z",
-     "shell.execute_reply": "2023-07-26T05:29:15.959066Z"
+     "iopub.execute_input": "2023-08-06T17:44:44.821358Z",
+     "iopub.status.busy": "2023-08-06T17:44:44.821244Z",
+     "iopub.status.idle": "2023-08-06T17:44:45.004111Z",
+     "shell.execute_reply": "2023-08-06T17:44:45.003828Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2107,7 +2107,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d29648ec",
+   "id": "81d8fa9f",
    "metadata": {},
    "source": [
     "Type  `subplots?` to learn more about \n",
@@ -2118,7 +2118,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2a6a0c9e",
+   "id": "d3760a25",
    "metadata": {},
    "source": [
     "To save the output of `fig`, we call its `savefig()`\n",
@@ -2129,13 +2129,13 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "id": "80e18950",
+   "id": "c86bffe6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:15.962416Z",
-     "iopub.status.busy": "2023-07-26T05:29:15.962231Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.048215Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.047676Z"
+     "iopub.execute_input": "2023-08-06T17:44:45.005700Z",
+     "iopub.status.busy": "2023-08-06T17:44:45.005580Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.085677Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.085363Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2147,7 +2147,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b8e17a71",
+   "id": "fd9dbb47",
    "metadata": {},
    "source": [
     "We can continue to modify `fig` using step-by-step updates; for example, we can modify the range of the $x$-axis, re-save the figure, and even re-display it. "
@@ -2156,13 +2156,13 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "id": "fe8c404d",
+   "id": "07f180e1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.051216Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.051042Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.330983Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.330378Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.087595Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.087433Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.317762Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.317456Z"
     }
    },
    "outputs": [
@@ -2186,7 +2186,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "55bff84e",
+   "id": "8e013a6f",
    "metadata": {},
    "source": [
     "We now create some more sophisticated plots. The \n",
@@ -2199,20 +2199,20 @@
     "* A matrix whose elements correspond to the `z` value (the third\n",
     "dimension) for each pair of `(x,y)` coordinates.\n",
     "\n",
-    "To create `x` and `y`, we’ll use the function `np.linspace()`. The command  `np.linspace(a, b, n)` \n",
-    "returns a vector of `n` numbers starting at  `a` and  ending at `b`."
+    "To create `x` and `y`, we’ll use the command  `np.linspace(a, b, n)`, \n",
+    "which returns a vector of `n` numbers starting at  `a` and  ending at `b`."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 50,
-   "id": "a99034cb",
+   "id": "a465c3aa",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.333539Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.333339Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.452013Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.451505Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.319492Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.319369Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.420916Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.420589Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2238,7 +2238,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fd6d00e6",
+   "id": "df35daed",
    "metadata": {},
    "source": [
     "We can increase the resolution by adding more levels to the image."
@@ -2247,13 +2247,13 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "id": "c613a5df",
+   "id": "469979b0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.454682Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.454485Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.604571Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.604143Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.422857Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.422743Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.549561Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.549260Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2276,7 +2276,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c1f2c4bd",
+   "id": "e6aa9a72",
    "metadata": {},
    "source": [
     "To fine-tune the output of the\n",
@@ -2293,13 +2293,13 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "id": "bef21527",
+   "id": "31092abb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.607805Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.607474Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.731227Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.730768Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.551373Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.551279Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.654104Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.653775Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2322,7 +2322,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "35ed7b29",
+   "id": "aba44db2",
    "metadata": {},
    "source": [
     "## Sequences and Slice Notation"
@@ -2330,7 +2330,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bb0cee76",
+   "id": "f0edc818",
    "metadata": {},
    "source": [
     "As seen above, the\n",
@@ -2341,13 +2341,13 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "id": "4435ed50",
+   "id": "4e834c17",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.733591Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.733437Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.736896Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.736428Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.655794Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.655683Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.658245Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.657943Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2370,7 +2370,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f1495e1b",
+   "id": "e95ff002",
    "metadata": {},
    "source": [
     "The function `np.arange()`\n",
@@ -2381,13 +2381,13 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "id": "7a2c664a",
+   "id": "65d67d22",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.739070Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.738902Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.742002Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.741608Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.659770Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.659662Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.661932Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.661619Z"
     }
    },
    "outputs": [
@@ -2409,7 +2409,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7b0e1b2f",
+   "id": "09d51db7",
    "metadata": {},
    "source": [
     "Why isn't $10$ output above? This has to do with *slice* notation in `Python`. \n",
@@ -2422,13 +2422,13 @@
   {
    "cell_type": "code",
    "execution_count": 55,
-   "id": "810eafdf",
+   "id": "676ab564",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.744281Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.744099Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.747188Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.746807Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.663547Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.663431Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.665689Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.665413Z"
     },
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    },
@@ -2450,7 +2450,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d73d0b54",
+   "id": "d51b85fc",
    "metadata": {},
    "source": [
     "In the code block above, the notation `3:6` is shorthand for  `slice(3,6)` when used inside\n",
@@ -2460,13 +2460,13 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "id": "f7a9f652",
+   "id": "569f45ab",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.749618Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.749428Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.752320Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.751846Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.667253Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.667154Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.669257Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.669007Z"
     }
    },
    "outputs": [
@@ -2487,7 +2487,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "be578cf4",
+   "id": "b82b891c",
    "metadata": {},
    "source": [
     "You might have expected  `slice(3,6)` to output the fourth through seventh characters in the text string (recalling that  `Python` begins its indexing at zero),  but instead it output  the fourth through sixth. \n",
@@ -2517,7 +2517,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7a9c183a",
+   "id": "46aa45f7",
    "metadata": {},
    "source": [
     "## Indexing Data\n",
@@ -2527,13 +2527,13 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "id": "24427538",
+   "id": "7cf343bd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.754673Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.754528Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.758000Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.757315Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.670804Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.670697Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.673052Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.672801Z"
     }
    },
    "outputs": [
@@ -2558,7 +2558,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d2c583a0",
+   "id": "a396d5a6",
    "metadata": {},
    "source": [
     "Typing `A[1,2]` retrieves the element corresponding to the second row and third\n",
@@ -2568,13 +2568,13 @@
   {
    "cell_type": "code",
    "execution_count": 58,
-   "id": "18684ed5",
+   "id": "2f4c1b37",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.760251Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.760111Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.763156Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.762782Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.674647Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.674533Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.676931Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.676679Z"
     }
    },
    "outputs": [
@@ -2595,7 +2595,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b25734ec",
+   "id": "839feee0",
    "metadata": {},
    "source": [
     "The first number after the open-bracket symbol `[`\n",
@@ -2609,13 +2609,13 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "id": "34d27b73",
+   "id": "a8ef1be5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.765326Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.765144Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.768118Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.767768Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.678456Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.678345Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.680588Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.680306Z"
     }
    },
    "outputs": [
@@ -2637,7 +2637,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "97149703",
+   "id": "abe68415",
    "metadata": {},
    "source": [
     "To select the first and third columns, we pass in  `[0,2]` as the second argument in the square brackets.\n",
@@ -2648,13 +2648,13 @@
   {
    "cell_type": "code",
    "execution_count": 60,
-   "id": "1bb799c5",
+   "id": "830897a9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.770122Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.769970Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.773095Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.772652Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.682117Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.682023Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.684256Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.683990Z"
     }
    },
    "outputs": [
@@ -2678,7 +2678,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b9ce4a3",
+   "id": "004f3600",
    "metadata": {},
    "source": [
     "Now, suppose that we want to select the submatrix made up of the second and fourth \n",
@@ -2689,13 +2689,13 @@
   {
    "cell_type": "code",
    "execution_count": 61,
-   "id": "de853e7c",
+   "id": "12e88036",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.775350Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.775182Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.778160Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.777807Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.685848Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.685735Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.687944Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.687676Z"
     }
    },
    "outputs": [
@@ -2716,22 +2716,22 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dd57a0bf",
+   "id": "9b978348",
    "metadata": {},
    "source": [
-    " Oops --- what happened? We got a one-dimensional array of length 2 identical to"
+    " Oops --- what happened? We got a one-dimensional array of length two identical to"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 62,
-   "id": "e71bf672",
+   "id": "c4098144",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.780228Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.780099Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.783205Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.782588Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.689456Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.689356Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.691673Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.691401Z"
     }
    },
    "outputs": [
@@ -2752,7 +2752,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9cd50d44",
+   "id": "2dcd98eb",
    "metadata": {},
    "source": [
     " Similarly,  the following code fails to extract the submatrix comprised of the second and fourth rows and the first, third, and fourth columns:"
@@ -2761,13 +2761,13 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "id": "458fe5c9",
+   "id": "b4d6bd49",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.785646Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.785525Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.812781Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.812287Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.693166Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.693066Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.715905Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.715629Z"
     }
    },
    "outputs": [
@@ -2789,7 +2789,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "67657309",
+   "id": "dcac422f",
    "metadata": {},
    "source": [
     "We can see what has gone wrong here. When supplied with two indexing lists, the `numpy` interpretation is that these provide pairs of $i,j$ indices for a series of entries. That is why the pair of lists must have the same length. However, that was not our intent, since we are looking for a submatrix.\n",
@@ -2800,13 +2800,13 @@
   {
    "cell_type": "code",
    "execution_count": 64,
-   "id": "703832ac",
+   "id": "e46c3267",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.815878Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.815556Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.819079Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.818526Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.717564Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.717458Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.719793Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.719525Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2829,7 +2829,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "00c8816e",
+   "id": "d14bb320",
    "metadata": {},
    "source": [
     "    "
@@ -2837,7 +2837,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "25c3a988",
+   "id": "a3d7e667",
    "metadata": {},
    "source": [
     "There are more efficient ways of achieving the same result.\n",
@@ -2849,13 +2849,13 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "id": "dbf328b7",
+   "id": "96d2355e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.821663Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.821485Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.825110Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.824596Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.721325Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.721214Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.723623Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.723345Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2879,7 +2879,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "13f73d32",
+   "id": "d462675f",
    "metadata": {},
    "source": [
     "Alternatively, we can subset matrices efficiently using slices.\n",
@@ -2892,13 +2892,13 @@
   {
    "cell_type": "code",
    "execution_count": 66,
-   "id": "65784eb0",
+   "id": "326ef740",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.827692Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.827506Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.830968Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.830460Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.725067Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.724962Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.727352Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.727075Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2921,7 +2921,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "63980dff",
+   "id": "e2eeed28",
    "metadata": {},
    "source": [
     "    "
@@ -2929,7 +2929,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "481bc57a",
+   "id": "5139b99f",
    "metadata": {},
    "source": [
     "Why are we able to retrieve a submatrix directly using slices but not using lists?\n",
@@ -2951,7 +2951,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f1c55b8a",
+   "id": "417c640e",
    "metadata": {},
    "source": [
     "### Boolean Indexing\n",
@@ -2962,13 +2962,13 @@
   {
    "cell_type": "code",
    "execution_count": 67,
-   "id": "3ddb0d83",
+   "id": "62ad65f2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.833837Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.833652Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.836642Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.836240Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.728977Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.728881Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.731155Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.730869Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2991,7 +2991,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f3007c8d",
+   "id": "117d1718",
    "metadata": {},
    "source": [
     "We now set two of the elements to `True`. "
@@ -3000,13 +3000,13 @@
   {
    "cell_type": "code",
    "execution_count": 68,
-   "id": "90e72009",
+   "id": "683f49a3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.839230Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.839048Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.844524Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.841903Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.732749Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.732642Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.734812Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.734546Z"
     }
    },
    "outputs": [
@@ -3028,7 +3028,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "932dac22",
+   "id": "5036e0f2",
    "metadata": {},
    "source": [
     "Note that the elements of `keep_rows`, when viewed as integers, are the same as the\n",
@@ -3039,13 +3039,13 @@
   {
    "cell_type": "code",
    "execution_count": 69,
-   "id": "fb3b6534",
+   "id": "ede73656",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.847591Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.847413Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.851043Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.850650Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.736256Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.736141Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.738461Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.738206Z"
     }
    },
    "outputs": [
@@ -3066,7 +3066,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8cb48c0",
+   "id": "45587df2",
    "metadata": {},
    "source": [
     "(Here, the function `np.all()` has checked whether\n",
@@ -3075,7 +3075,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ac824821",
+   "id": "cd3e2b53",
    "metadata": {},
    "source": [
     "   However, even though `np.array([0,1,0,1])`  and `keep_rows` are equal according to `==`, they index different sets of rows!\n",
@@ -3085,13 +3085,13 @@
   {
    "cell_type": "code",
    "execution_count": 70,
-   "id": "b146db22",
+   "id": "f65c75d6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.854162Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.853950Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.860504Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.860073Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.740063Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.739965Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.742303Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.742014Z"
     }
    },
    "outputs": [
@@ -3115,7 +3115,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0b18644",
+   "id": "12479298",
    "metadata": {},
    "source": [
     " By contrast, `keep_rows` retrieves only the second and fourth rows  of `A` --- i.e. the rows for which the Boolean equals `TRUE`. "
@@ -3124,13 +3124,13 @@
   {
    "cell_type": "code",
    "execution_count": 71,
-   "id": "6bf7b4a3",
+   "id": "31a8ff76",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.864709Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.864481Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.869279Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.868135Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.743800Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.743693Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.745942Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.745692Z"
     }
    },
    "outputs": [
@@ -3152,7 +3152,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "80686b74",
+   "id": "40932333",
    "metadata": {},
    "source": [
     "This example shows that Booleans and integers are treated differently by `numpy`."
@@ -3160,7 +3160,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d7905166",
+   "id": "8751cf99",
    "metadata": {},
    "source": [
     "We again make use of the `np.ix_()` function\n",
@@ -3171,13 +3171,13 @@
   {
    "cell_type": "code",
    "execution_count": 72,
-   "id": "288011d9",
+   "id": "c91f330e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.875531Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.874719Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.880224Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.879831Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.747553Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.747444Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.750009Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.749713Z"
     }
    },
    "outputs": [
@@ -3202,7 +3202,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "37900313",
+   "id": "e8b9619b",
    "metadata": {},
    "source": [
     "We can also mix a list with an array of Booleans in the arguments to `np.ix_()`:"
@@ -3211,13 +3211,13 @@
   {
    "cell_type": "code",
    "execution_count": 73,
-   "id": "3e3b1954",
+   "id": "fb53de70",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.885549Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.885336Z",
-     "iopub.status.idle": "2023-07-26T05:29:17.890989Z",
-     "shell.execute_reply": "2023-07-26T05:29:17.890528Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.751453Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.751351Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.753544Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.753283Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3241,7 +3241,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c679e7b",
+   "id": "18f16a0a",
    "metadata": {},
    "source": [
     "    "
@@ -3249,7 +3249,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2f4d70f3",
+   "id": "f6e932f4",
    "metadata": {},
    "source": [
     "For more details on indexing in `numpy`, readers are referred\n",
@@ -3258,7 +3258,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3c59c8fb",
+   "id": "8c59352f",
    "metadata": {},
    "source": [
     "## Loading Data\n",
@@ -3275,7 +3275,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "95297c29",
+   "id": "4417d4d4",
    "metadata": {},
    "source": [
     "### Reading in a Data Set\n",
@@ -3294,7 +3294,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "42760180",
+   "id": "f9fd0896",
    "metadata": {},
    "source": [
     "We will begin by reading in `Auto.csv`, available on the book website. This is a comma-separated file, and can be read in using `pd.read_csv()`: "
@@ -3303,13 +3303,13 @@
   {
    "cell_type": "code",
    "execution_count": 74,
-   "id": "d02bfb28",
+   "id": "cc87ed8c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:17.893962Z",
-     "iopub.status.busy": "2023-07-26T05:29:17.893772Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.126793Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.126353Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.755171Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.755065Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.984772Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.984442Z"
     }
    },
    "outputs": [
@@ -3526,7 +3526,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5acc3596",
+   "id": "5c4cf682",
    "metadata": {},
    "source": [
     "The book website also has a whitespace-delimited version of this data, called `Auto.data`. This can be read in as follows:"
@@ -3535,13 +3535,13 @@
   {
    "cell_type": "code",
    "execution_count": 75,
-   "id": "ca6090af",
+   "id": "69b34e00",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.129214Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.129036Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.133861Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.133327Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.986269Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.986168Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.989605Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.989331Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3552,7 +3552,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "350f1f42",
+   "id": "61b12987",
    "metadata": {},
    "source": [
     " Both `Auto.csv` and `Auto.data` are simply text\n",
@@ -3563,7 +3563,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1cae3ad2",
+   "id": "8de34877",
    "metadata": {},
    "source": [
     "We now take a look at the column of `Auto` corresponding to the variable `horsepower`: "
@@ -3572,13 +3572,13 @@
   {
    "cell_type": "code",
    "execution_count": 76,
-   "id": "7220aa87",
+   "id": "c45b3e32",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.136921Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.136464Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.140452Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.139936Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.991142Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.991052Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.993697Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.993441Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3611,7 +3611,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0adabf1",
+   "id": "7b5df8f9",
    "metadata": {},
    "source": [
     "We see that the `dtype` of this column is `object`. \n",
@@ -3623,13 +3623,13 @@
   {
    "cell_type": "code",
    "execution_count": 77,
-   "id": "ca1939f0",
+   "id": "fdac0ada",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.142925Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.142803Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.146461Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.145934Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.995126Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.995036Z",
+     "iopub.status.idle": "2023-08-06T17:44:46.997375Z",
+     "shell.execute_reply": "2023-08-06T17:44:46.997124Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3664,7 +3664,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c35e48dc",
+   "id": "dc6e92aa",
    "metadata": {},
    "source": [
     "We see the culprit is the value `?`, which is being used to encode missing values.\n",
@@ -3673,7 +3673,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ccf8e5de",
+   "id": "f15457ad",
    "metadata": {},
    "source": [
     "To fix the problem, we must provide `pd.read_csv()` with an argument called `na_values`.\n",
@@ -3684,13 +3684,13 @@
   {
    "cell_type": "code",
    "execution_count": 78,
-   "id": "cfb084e7",
+   "id": "883e0b73",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.149045Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.148875Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.153953Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.153625Z"
+     "iopub.execute_input": "2023-08-06T17:44:46.998839Z",
+     "iopub.status.busy": "2023-08-06T17:44:46.998751Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.002360Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.002105Z"
     },
     "lines_to_next_cell": 2
    },
@@ -3715,7 +3715,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2e8e504f",
+   "id": "cbc53f2a",
    "metadata": {},
    "source": [
     "The `Auto.shape`  attribute tells us that the data has 397\n",
@@ -3725,13 +3725,13 @@
   {
    "cell_type": "code",
    "execution_count": 79,
-   "id": "2e02b6a5",
+   "id": "c733c1e8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.156574Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.155920Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.159130Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.158724Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.003760Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.003683Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.005701Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.005460Z"
     }
    },
    "outputs": [
@@ -3752,7 +3752,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "df109192",
+   "id": "94c32cfb",
    "metadata": {},
    "source": [
     "There are\n",
@@ -3764,13 +3764,13 @@
   {
    "cell_type": "code",
    "execution_count": 80,
-   "id": "d391f8d0",
+   "id": "0e0e9956",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.161446Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.161286Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.165230Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.164876Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.007197Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.007116Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.009545Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.009321Z"
     },
     "lines_to_next_cell": 2
    },
@@ -3793,7 +3793,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e1ddfb53",
+   "id": "7250498b",
    "metadata": {},
    "source": [
     "### Basics of Selecting Rows and Columns\n",
@@ -3804,13 +3804,13 @@
   {
    "cell_type": "code",
    "execution_count": 81,
-   "id": "a222ca60",
+   "id": "0477b4ff",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.167288Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.167156Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.171499Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.171112Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.010883Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.010793Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.012894Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.012633Z"
     },
     "lines_to_next_cell": 2
    },
@@ -3835,7 +3835,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "be6f2daf",
+   "id": "c2084300",
    "metadata": {},
    "source": [
     "Accessing the rows and columns of a data frame is similar, but not identical, to accessing the rows and columns of an array. \n",
@@ -3848,13 +3848,13 @@
   {
    "cell_type": "code",
    "execution_count": 82,
-   "id": "a75921ac",
+   "id": "a989e541",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.173985Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.173779Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.180116Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.179681Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.014269Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.014179Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.018504Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.018245Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3955,7 +3955,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "17c02ad7",
+   "id": "b5af114e",
    "metadata": {},
    "source": [
     "Similarly, an array of Booleans can be used to subset the rows:"
@@ -3964,13 +3964,13 @@
   {
    "cell_type": "code",
    "execution_count": 83,
-   "id": "7469ff2b",
+   "id": "d336e7ce",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.183321Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.183157Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.201363Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.200939Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.019899Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.019821Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.032395Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.032144Z"
     },
     "lines_to_next_cell": 0
    },
@@ -4842,7 +4842,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "27eb1780",
+   "id": "2f09c4df",
    "metadata": {},
    "source": [
     "However, if we pass  in a list of strings to the `[]` method, then we obtain a data frame containing the corresponding set of *columns*. "
@@ -4851,13 +4851,13 @@
   {
    "cell_type": "code",
    "execution_count": 84,
-   "id": "ac455404",
+   "id": "88e9a63b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.203476Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.203352Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.209504Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.209134Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.033786Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.033705Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.038029Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.037800Z"
     },
     "lines_to_next_cell": 0
    },
@@ -4976,7 +4976,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1629d302",
+   "id": "b372687d",
    "metadata": {},
    "source": [
     "Since we did not specify an *index* column when we loaded our data frame, the rows are labeled using integers\n",
@@ -4986,13 +4986,13 @@
   {
    "cell_type": "code",
    "execution_count": 85,
-   "id": "f41235d4",
+   "id": "aed049d8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.211995Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.211814Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.215209Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.214581Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.039393Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.039316Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.041519Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.041279Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5017,7 +5017,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "79d3cebb",
+   "id": "f18f3695",
    "metadata": {},
    "source": [
     "We can use the\n",
@@ -5027,13 +5027,13 @@
   {
    "cell_type": "code",
    "execution_count": 86,
-   "id": "31caba24",
+   "id": "c93cefd3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.217421Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.217292Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.225169Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.224781Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.043059Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.042954Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.048986Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.048726Z"
     }
    },
    "outputs": [
@@ -5251,13 +5251,13 @@
   {
    "cell_type": "code",
    "execution_count": 87,
-   "id": "594bedfa",
+   "id": "84947a78",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.227488Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.227297Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.230280Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.229861Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.050266Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.050189Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.052314Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.052075Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5281,7 +5281,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "184977f2",
+   "id": "fc160806",
    "metadata": {},
    "source": [
     "We see that the column `'name'` is no longer there.\n",
@@ -5294,13 +5294,13 @@
   {
    "cell_type": "code",
    "execution_count": 88,
-   "id": "9a59b083",
+   "id": "7ee59fae",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.232510Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.232342Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.238242Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.237748Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.053681Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.053604Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.057791Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.057552Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5398,7 +5398,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "066af73b",
+   "id": "232fe34c",
    "metadata": {},
    "source": [
     "As an alternative to using the index name, we could retrieve the 4th and 5th rows of `Auto` using the `{iloc[]`} method:"
@@ -5407,13 +5407,13 @@
   {
    "cell_type": "code",
    "execution_count": 89,
-   "id": "54457a11",
+   "id": "4b5a0e01",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.240468Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.240293Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.245745Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.245311Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.059126Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.059053Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.063134Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.062896Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5510,7 +5510,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "069ca71e",
+   "id": "6c409a01",
    "metadata": {},
    "source": [
     "We can also use it to retrieve the 1st, 3rd and and 4th columns of `Auto_re`:"
@@ -5519,13 +5519,13 @@
   {
    "cell_type": "code",
    "execution_count": 90,
-   "id": "8a4f3faf",
+   "id": "8814803e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.247984Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.247834Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.254533Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.254012Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.064565Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.064486Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.069061Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.068830Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5663,7 +5663,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c6f4f9a2",
+   "id": "f02f0d24",
    "metadata": {},
    "source": [
     "We can extract the 4th and 5th rows, as well as the 1st, 3rd and 4th columns, using\n",
@@ -5673,13 +5673,13 @@
   {
    "cell_type": "code",
    "execution_count": 91,
-   "id": "8f1e6e56",
+   "id": "c7567dd0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.256972Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.256754Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.261662Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.261232Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.070446Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.070375Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.073852Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.073601Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5751,7 +5751,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6e4b778c",
+   "id": "3073ab09",
    "metadata": {},
    "source": [
     "Index entries need not be unique: there are several cars  in the data frame named `ford galaxie 500`."
@@ -5760,13 +5760,13 @@
   {
    "cell_type": "code",
    "execution_count": 92,
-   "id": "f1d0e795",
+   "id": "63638341",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.263825Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.263676Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.268126Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.267724Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.075218Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.075139Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.078529Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.078280Z"
     },
     "lines_to_next_cell": 0
    },
@@ -5840,7 +5840,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b10eabb7",
+   "id": "2fbe4a9b",
    "metadata": {},
    "source": [
     "### More on Selecting Rows and Columns\n",
@@ -5853,13 +5853,13 @@
   {
    "cell_type": "code",
    "execution_count": 93,
-   "id": "392f10a1",
+   "id": "57d6de11",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.270321Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.270149Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.277370Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.276917Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.079924Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.079849Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.085281Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.085034Z"
     },
     "lines_to_next_cell": 2
    },
@@ -6264,7 +6264,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d3f85975",
+   "id": "a58067ce",
    "metadata": {},
    "source": [
     "To do this more concisely, we can use an anonymous function called a `lambda`: "
@@ -6273,13 +6273,13 @@
   {
    "cell_type": "code",
    "execution_count": 94,
-   "id": "5f5b7906",
+   "id": "ed95866c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.279435Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.279296Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.287423Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.286943Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.086682Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.086607Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.092129Z",
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@@ -6683,7 +6683,7 @@
   },
   {
    "cell_type": "markdown",
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    "metadata": {},
    "source": [
     "The `lambda` call creates a function that takes a single\n",
@@ -6697,13 +6697,13 @@
   {
    "cell_type": "code",
    "execution_count": 95,
-   "id": "b13c5728",
+   "id": "e3725c98",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.289828Z",
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-     "shell.execute_reply": "2023-07-26T05:29:18.295846Z"
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@@ -6965,7 +6965,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7885bba9",
+   "id": "6da7a099",
    "metadata": {},
    "source": [
     "The symbol `&` computes an element-wise *and* operation.\n",
@@ -6977,13 +6977,13 @@
   {
    "cell_type": "code",
    "execution_count": 96,
-   "id": "d5a2c3be",
+   "id": "f617c333",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.298956Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.298779Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.306530Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.305978Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.099319Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.099241Z",
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@@ -7349,7 +7349,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8a7a6c62",
+   "id": "924428a0",
    "metadata": {},
    "source": [
     "Here, the symbol `|` computes an element-wise *or* operation.\n",
@@ -7368,13 +7368,13 @@
   {
    "cell_type": "code",
    "execution_count": 97,
-   "id": "a6278441",
+   "id": "17f13a72",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.308697Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.308549Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.311058Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.310729Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.106536Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.106458Z",
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@@ -7396,7 +7396,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "92948288",
+   "id": "15f0c1b1",
    "metadata": {},
    "source": [
     "The indented code beneath the line with the `for` statement is run\n",
@@ -7412,13 +7412,13 @@
   {
    "cell_type": "code",
    "execution_count": 98,
-   "id": "2aa065a8",
+   "id": "07e6a011",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.313814Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.313627Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.316245Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.315821Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.109780Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.109691Z",
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@@ -7441,7 +7441,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aaeb60c5",
+   "id": "fd8124cb",
    "metadata": {},
    "source": [
     "Above, we summed over each combination of `value` and `weight`.\n",
@@ -7464,13 +7464,13 @@
   {
    "cell_type": "code",
    "execution_count": 99,
-   "id": "832c1b7d",
+   "id": "377ab16f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.318251Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.318060Z",
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-     "shell.execute_reply": "2023-07-26T05:29:18.321594Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.113038Z",
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+     "iopub.status.idle": "2023-08-06T17:44:47.114837Z",
+     "shell.execute_reply": "2023-08-06T17:44:47.114609Z"
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@@ -7492,7 +7492,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ac163d59",
+   "id": "345a595b",
    "metadata": {},
    "source": [
     "### String Formatting\n",
@@ -7519,13 +7519,13 @@
   {
    "cell_type": "code",
    "execution_count": 100,
-   "id": "2ca2e7cd",
+   "id": "91276344",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.324105Z",
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-     "iopub.status.idle": "2023-07-26T05:29:18.330121Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.329787Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.116243Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.116152Z",
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@@ -7615,13 +7615,13 @@
   {
    "cell_type": "code",
    "execution_count": 101,
-   "id": "d8ae1dcc",
+   "id": "c655fcd1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.332238Z",
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-     "shell.execute_reply": "2023-07-26T05:29:18.335131Z"
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@@ -7647,7 +7647,7 @@
   },
   {
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    "source": [
     "We see that the `template.format()` method expects two arguments `{0}`\n",
@@ -7661,7 +7661,7 @@
   },
   {
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-   "id": "22226024",
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    "metadata": {},
    "source": [
     "## Additional Graphical and Numerical Summaries\n",
@@ -7672,13 +7672,13 @@
   {
    "cell_type": "code",
    "execution_count": 102,
-   "id": "30a8a663",
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     "execution": {
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@@ -7712,7 +7712,7 @@
   },
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-   "id": "f09f4e10",
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    "source": [
     "We can address this by accessing the columns directly:"
@@ -7721,13 +7721,13 @@
   {
    "cell_type": "code",
    "execution_count": 103,
-   "id": "81fdedb1",
+   "id": "49d239e5",
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     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.452711Z",
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-     "shell.execute_reply": "2023-07-26T05:29:18.556309Z"
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@@ -7750,7 +7750,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a64455fa",
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    "metadata": {},
    "source": [
     "Alternatively, we can use the `plot()` method with the call `Auto.plot()`.\n",
@@ -7763,25 +7763,17 @@
   {
    "cell_type": "code",
    "execution_count": 104,
-   "id": "61850515",
+   "id": "5c892a6a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.559255Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.559034Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.680294Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.679833Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.310772Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.310600Z",
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     },
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    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pandas/plotting/_matplotlib/core.py:1114: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n",
-      "  scatter = ax.scatter(\n"
-     ]
-    },
     {
      "data": {
       "text/plain": [
@@ -7810,7 +7802,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7c73790f",
+   "id": "74ed42da",
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    "source": [
     "If we want to save\n",
@@ -7821,13 +7813,13 @@
   {
    "cell_type": "code",
    "execution_count": 105,
-   "id": "f2e0c165",
+   "id": "92a626b0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.682678Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.682519Z",
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-     "shell.execute_reply": "2023-07-26T05:29:18.726384Z"
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     }
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@@ -7838,7 +7830,7 @@
   },
   {
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+   "id": "7c47c9a8",
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    "source": [
     "We can further instruct the data frame to plot to a particular axes object. In this\n",
@@ -7852,13 +7844,13 @@
   {
    "cell_type": "code",
    "execution_count": 106,
-   "id": "35c72e77",
+   "id": "bf9771b9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.729555Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.729403Z",
-     "iopub.status.idle": "2023-07-26T05:29:18.935439Z",
-     "shell.execute_reply": "2023-07-26T05:29:18.934984Z"
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     }
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@@ -7880,7 +7872,7 @@
   },
   {
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-   "id": "95b0f3de",
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    "source": [
     "Note also that the columns of a data frame can be accessed as attributes: try typing in `Auto.horsepower`. "
@@ -7888,7 +7880,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5c6c4fa2",
+   "id": "7d4e028a",
    "metadata": {},
    "source": [
     "We now consider the `cylinders` variable. Typing in `Auto.cylinders.dtype` reveals that it is being treated as a quantitative variable. \n",
@@ -7900,13 +7892,13 @@
   {
    "cell_type": "code",
    "execution_count": 107,
-   "id": "2b6fb1ad",
+   "id": "745d2c5f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.937842Z",
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-     "shell.execute_reply": "2023-07-26T05:29:18.941344Z"
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+     "iopub.status.busy": "2023-08-06T17:44:47.624220Z",
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@@ -7929,7 +7921,7 @@
   },
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-   "id": "2038c16d",
+   "id": "d9c6dc9e",
    "metadata": {},
    "source": [
     " Now that `cylinders` is qualitative, we can display it using\n",
@@ -7939,13 +7931,13 @@
   {
    "cell_type": "code",
    "execution_count": 108,
-   "id": "1f19f48c",
+   "id": "8b1069bc",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:18.944261Z",
-     "iopub.status.busy": "2023-07-26T05:29:18.944131Z",
-     "iopub.status.idle": "2023-07-26T05:29:19.068255Z",
-     "shell.execute_reply": "2023-07-26T05:29:19.067715Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.629273Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.629176Z",
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+     "shell.execute_reply": "2023-08-06T17:44:47.735790Z"
     }
    },
    "outputs": [
@@ -7967,7 +7959,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4ae72e1b",
+   "id": "f96288b4",
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    "source": [
     "The `hist()`  method can be used to plot a *histogram*."
@@ -7976,13 +7968,13 @@
   {
    "cell_type": "code",
    "execution_count": 109,
-   "id": "929b6901",
+   "id": "d9faa85a",
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-     "shell.execute_reply": "2023-07-26T05:29:19.194542Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.737744Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.737633Z",
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@@ -8005,7 +7997,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "db7f6e7c",
+   "id": "8f743bb2",
    "metadata": {},
    "source": [
     "The color of the bars and the number of bins can be changed:"
@@ -8014,13 +8006,13 @@
   {
    "cell_type": "code",
    "execution_count": 110,
-   "id": "8d48f1e9",
+   "id": "59d4a0b6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:19.197491Z",
-     "iopub.status.busy": "2023-07-26T05:29:19.197276Z",
-     "iopub.status.idle": "2023-07-26T05:29:19.318988Z",
-     "shell.execute_reply": "2023-07-26T05:29:19.318622Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.841851Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.841742Z",
+     "iopub.status.idle": "2023-08-06T17:44:47.938350Z",
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@@ -8043,7 +8035,7 @@
   },
   {
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-   "id": "0e53b8b6",
+   "id": "59d4f72f",
    "metadata": {},
    "source": [
     " See `Auto.hist?` for more plotting\n",
@@ -8056,13 +8048,13 @@
   {
    "cell_type": "code",
    "execution_count": 111,
-   "id": "400690e6",
+   "id": "fb5ed57d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:19.321439Z",
-     "iopub.status.busy": "2023-07-26T05:29:19.321240Z",
-     "iopub.status.idle": "2023-07-26T05:29:20.519159Z",
-     "shell.execute_reply": "2023-07-26T05:29:20.518700Z"
+     "iopub.execute_input": "2023-08-06T17:44:47.940123Z",
+     "iopub.status.busy": "2023-08-06T17:44:47.939990Z",
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@@ -8084,7 +8076,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "48a9a4f5",
+   "id": "7f671845",
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    "source": [
     " We can also produce scatterplots\n",
@@ -8094,13 +8086,13 @@
   {
    "cell_type": "code",
    "execution_count": 112,
-   "id": "6bbeca8b",
+   "id": "8e117e38",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:20.521548Z",
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-     "iopub.status.idle": "2023-07-26T05:29:20.804202Z",
-     "shell.execute_reply": "2023-07-26T05:29:20.803825Z"
+     "iopub.execute_input": "2023-08-06T17:44:48.896866Z",
+     "iopub.status.busy": "2023-08-06T17:44:48.896756Z",
+     "iopub.status.idle": "2023-08-06T17:44:49.119272Z",
+     "shell.execute_reply": "2023-08-06T17:44:49.118911Z"
     },
     "lines_to_next_cell": 0
    },
@@ -8124,7 +8116,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d3bb4736",
+   "id": "97921078",
    "metadata": {},
    "source": [
     "The `describe()`  method produces a numerical summary of each column in a data frame."
@@ -8133,13 +8125,13 @@
   {
    "cell_type": "code",
    "execution_count": 113,
-   "id": "1727f604",
+   "id": "9e0b12f2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:20.809656Z",
-     "iopub.status.busy": "2023-07-26T05:29:20.809455Z",
-     "iopub.status.idle": "2023-07-26T05:29:20.816572Z",
-     "shell.execute_reply": "2023-07-26T05:29:20.816157Z"
+     "iopub.execute_input": "2023-08-06T17:44:49.121032Z",
+     "iopub.status.busy": "2023-08-06T17:44:49.120921Z",
+     "iopub.status.idle": "2023-08-06T17:44:49.126814Z",
+     "shell.execute_reply": "2023-08-06T17:44:49.126535Z"
     },
     "lines_to_next_cell": 0
    },
@@ -8237,7 +8229,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1b508635",
+   "id": "93fc12de",
    "metadata": {},
    "source": [
     "We can also produce a summary of just a single column."
@@ -8246,13 +8238,13 @@
   {
    "cell_type": "code",
    "execution_count": 114,
-   "id": "39bf4091",
+   "id": "ba4aa0f6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:29:20.819204Z",
-     "iopub.status.busy": "2023-07-26T05:29:20.818991Z",
-     "iopub.status.idle": "2023-07-26T05:29:20.824216Z",
-     "shell.execute_reply": "2023-07-26T05:29:20.823857Z"
+     "iopub.execute_input": "2023-08-06T17:44:49.128408Z",
+     "iopub.status.busy": "2023-08-06T17:44:49.128319Z",
+     "iopub.status.idle": "2023-08-06T17:44:49.132582Z",
+     "shell.execute_reply": "2023-08-06T17:44:49.132299Z"
     },
     "lines_to_next_cell": 0
    },
@@ -8283,12 +8275,12 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22ecf5c3",
+   "id": "c029ae61",
    "metadata": {},
    "source": [
     "To exit `Jupyter`,  select `File / Close and Halt`.\n",
     "\n",
-    "\n",
+    " \n",
     "\n"
    ]
   }
@@ -8309,7 +8301,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/Ch3-linreg-lab.ipynb b/Ch3-linreg-lab.ipynb
index 72e3242..910b824 100644
--- a/Ch3-linreg-lab.ipynb
+++ b/Ch3-linreg-lab.ipynb
@@ -28,10 +28,10 @@
    "id": "ca5277a6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:48.562599Z",
-     "iopub.status.busy": "2023-07-26T05:16:48.562472Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.062186Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.061609Z"
+     "iopub.execute_input": "2023-08-06T17:34:45.279319Z",
+     "iopub.status.busy": "2023-08-06T17:34:45.279082Z",
+     "iopub.status.idle": "2023-08-06T17:34:45.953848Z",
+     "shell.execute_reply": "2023-08-06T17:34:45.953518Z"
     },
     "lines_to_next_cell": 2
    },
@@ -61,10 +61,10 @@
    "id": "675f24e6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.064676Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.064483Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.739307Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.738853Z"
+     "iopub.execute_input": "2023-08-06T17:34:45.955884Z",
+     "iopub.status.busy": "2023-08-06T17:34:45.955666Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.765820Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.765525Z"
     },
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    },
@@ -94,10 +94,10 @@
    "id": "a0ee23c2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.741758Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.741609Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.744969Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.744551Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.767689Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.767547Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.770326Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.770048Z"
     }
    },
    "outputs": [],
@@ -125,10 +125,10 @@
    "id": "b35eb887",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.747166Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.746991Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.867818Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.867356Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.771834Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.771733Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.958904Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.958467Z"
     }
    },
    "outputs": [],
@@ -157,10 +157,10 @@
    "id": "961908f7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.870378Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.870231Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.874355Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.873851Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.960948Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.960687Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.964347Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.964073Z"
     },
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    },
@@ -238,10 +238,10 @@
    "id": "662caa15",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.876620Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.876476Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.880485Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.880074Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.966063Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.965960Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.968939Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.968662Z"
     },
     "lines_to_next_cell": 0
    },
@@ -264,6 +264,7 @@
        " '__array_wrap__',\n",
        " '__bool__',\n",
        " '__class__',\n",
+       " '__class_getitem__',\n",
        " '__complex__',\n",
        " '__contains__',\n",
        " '__copy__',\n",
@@ -272,6 +273,8 @@
        " '__delitem__',\n",
        " '__dir__',\n",
        " '__divmod__',\n",
+       " '__dlpack__',\n",
+       " '__dlpack_device__',\n",
        " '__doc__',\n",
        " '__eq__',\n",
        " '__float__',\n",
@@ -280,6 +283,7 @@
        " '__ge__',\n",
        " '__getattribute__',\n",
        " '__getitem__',\n",
+       " '__getstate__',\n",
        " '__gt__',\n",
        " '__hash__',\n",
        " '__iadd__',\n",
@@ -438,10 +442,10 @@
    "id": "ebb7d126",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.882618Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.882477Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.885324Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.884886Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.970359Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.970263Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.972364Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.972124Z"
     },
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    },
@@ -496,10 +500,10 @@
    "id": "1ea46cee",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.887855Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.887580Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.892800Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.892442Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.973818Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.973741Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.982452Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.982201Z"
     }
    },
    "outputs": [
@@ -540,10 +544,10 @@
    "id": "26c0ba88",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.895108Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.894938Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.901385Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.900996Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.983850Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.983745Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.990247Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.990002Z"
     }
    },
    "outputs": [
@@ -630,10 +634,10 @@
    "id": "d4dd511b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.903600Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.903426Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.906235Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.905900Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.991664Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.991561Z",
+     "iopub.status.idle": "2023-08-06T17:34:46.994290Z",
+     "shell.execute_reply": "2023-08-06T17:34:46.994049Z"
     },
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    },
@@ -665,10 +669,10 @@
    "id": "eef9f8e3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.908149Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.908028Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.973872Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.973443Z"
+     "iopub.execute_input": "2023-08-06T17:34:46.995620Z",
+     "iopub.status.busy": "2023-08-06T17:34:46.995530Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.057569Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.057305Z"
     },
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    },
@@ -776,10 +780,10 @@
    "id": "557170d4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.976562Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.976352Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.982733Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.982315Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.059196Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.059050Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.063793Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.063548Z"
     },
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    },
@@ -871,10 +875,10 @@
    "id": "b83ec097",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.985396Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.985228Z",
-     "iopub.status.idle": "2023-07-26T05:16:49.992390Z",
-     "shell.execute_reply": "2023-07-26T05:16:49.991020Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.065239Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.065152Z",
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@@ -975,10 +979,10 @@
    "id": "d4dce5f6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:49.995458Z",
-     "iopub.status.busy": "2023-07-26T05:16:49.995307Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.003927Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.003569Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.070742Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.070666Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.079919Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.079672Z"
     }
    },
    "outputs": [
@@ -997,10 +1001,10 @@
        "  Method:             Least Squares    F-statistic:           601.6\n",
        "\n",
        "\n",
-       "  Date:             Tue, 25 Jul 2023   Prob (F-statistic): 5.08e-88\n",
+       "  Date:             Sun, 06 Aug 2023   Prob (F-statistic): 5.08e-88\n",
        "\n",
        "\n",
-       "  Time:                 22:16:49       Log-Likelihood:      -1641.5\n",
+       "  Time:                 10:34:47       Log-Likelihood:      -1641.5\n",
        "\n",
        "\n",
        "  No. Observations:         506        AIC:                   3287.\n",
@@ -1041,6 +1045,41 @@
        "\n",
        "

Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
       ],
+      "text/latex": [
+       "\\begin{center}\n",
+       "\\begin{tabular}{lclc}\n",
+       "\\toprule\n",
+       "\\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, 06 Aug 2023 & \\textbf{  Prob (F-statistic):} &  5.08e-88   \\\\\n",
+       "\\textbf{Time:}             &     10:34:47     & \\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",
+       "\\textbf{Covariance Type:}  &    nonrobust     & \\textbf{                     } &             \\\\\n",
+       "\\bottomrule\n",
+       "\\end{tabular}\n",
+       "\\begin{tabular}{lcccccc}\n",
+       "                   & \\textbf{coef} & \\textbf{std err} & \\textbf{t} & \\textbf{P$> |$t$|$} & \\textbf{[0.025} & \\textbf{0.975]}  \\\\\n",
+       "\\midrule\n",
+       "\\textbf{intercept} &      34.5538  &        0.563     &    61.415  &         0.000        &       33.448    &       35.659     \\\\\n",
+       "\\textbf{lstat}     &      -0.9500  &        0.039     &   -24.528  &         0.000        &       -1.026    &       -0.874     \\\\\n",
+       "\\bottomrule\n",
+       "\\end{tabular}\n",
+       "\\begin{tabular}{lclc}\n",
+       "\\textbf{Omnibus:}       & 137.043 & \\textbf{  Durbin-Watson:     } &    0.892  \\\\\n",
+       "\\textbf{Prob(Omnibus):} &   0.000 & \\textbf{  Jarque-Bera (JB):  } &  291.373  \\\\\n",
+       "\\textbf{Skew:}          &   1.453 & \\textbf{  Prob(JB):          } & 5.36e-64  \\\\\n",
+       "\\textbf{Kurtosis:}      &   5.319 & \\textbf{  Cond. No.          } &     29.7  \\\\\n",
+       "\\bottomrule\n",
+       "\\end{tabular}\n",
+       "%\\caption{OLS Regression Results}\n",
+       "\\end{center}\n",
+       "\n",
+       "Notes: \\newline\n",
+       " [1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
+      ],
       "text/plain": [
        "\n",
        "\"\"\"\n",
@@ -1049,8 +1088,8 @@
        "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:                Tue, 25 Jul 2023   Prob (F-statistic):           5.08e-88\n",
-       "Time:                        22:16:49   Log-Likelihood:                -1641.5\n",
+       "Date:                Sun, 06 Aug 2023   Prob (F-statistic):           5.08e-88\n",
+       "Time:                        10:34:47   Log-Likelihood:                -1641.5\n",
        "No. Observations:                 506   AIC:                             3287.\n",
        "Df Residuals:                     504   BIC:                             3295.\n",
        "Df Model:                           1                                         \n",
@@ -1096,10 +1135,10 @@
    "id": "a0edf555",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.006397Z",
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-     "shell.execute_reply": "2023-07-26T05:16:50.009037Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.081336Z",
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    },
@@ -1139,10 +1178,10 @@
    "id": "fdc5a3f3",
    "metadata": {
     "execution": {
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-     "iopub.status.idle": "2023-07-26T05:16:50.016842Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.016427Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.085093Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.085015Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.088625Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.088392Z"
     }
    },
    "outputs": [
@@ -1223,10 +1262,10 @@
    "id": "2c6acbf0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.019127Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.018964Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.022350Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.021918Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.090091Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.090008Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.092428Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.092183Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1261,10 +1300,10 @@
    "id": "c472ef33",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.024574Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.024433Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.027837Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.027439Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.093785Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.093688Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.096010Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.095781Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1300,10 +1339,10 @@
    "id": "3e2ffc7a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.029978Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.029838Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.032847Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.032491Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.097324Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.097234Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.099513Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.099275Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1360,10 +1399,10 @@
    "id": "4e56a1d3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.035185Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.035076Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.037782Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.037389Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.100972Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.100892Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.102793Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.102549Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1394,10 +1433,10 @@
    "id": "7f43ffe7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.040033Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.039836Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.042447Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.042026Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.104148Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.104079Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.106062Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.105836Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1434,22 +1473,14 @@
    "id": "3f7b67c9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.044790Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.044610Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.159032Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.158476Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.107460Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.107386Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.254700Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.253915Z"
     },
     "lines_to_next_cell": 0
    },
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/pandas/plotting/_matplotlib/core.py:1114: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n",
-      "  scatter = ax.scatter(\n"
-     ]
-    },
     {
      "data": {
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",
@@ -1506,10 +1537,10 @@
    "id": "b35a2fd3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.161898Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.161592Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.274404Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.273842Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.259557Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.259229Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.402403Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.402135Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1554,10 +1585,10 @@
    "id": "82673b80",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.276799Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.276637Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.384102Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.383325Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.404190Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.404052Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.494230Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.493905Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1622,10 +1653,10 @@
    "id": "54596dc4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.387053Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.386874Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.400398Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.399938Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.495999Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.495872Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.506251Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.505979Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1720,10 +1751,10 @@
    "id": "75c78238",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.402974Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.402819Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.406561Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.406042Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.508238Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.508087Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.510826Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.510491Z"
     }
    },
    "outputs": [
@@ -1760,10 +1791,10 @@
    "id": "f14b9e1a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.409092Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.408922Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.427019Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.426146Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.512561Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.512448Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.526980Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.526612Z"
     }
    },
    "outputs": [
@@ -1936,10 +1967,10 @@
    "id": "0a2714b1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.430858Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.430692Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.449487Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.448800Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.528637Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.528526Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.542270Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.541976Z"
     }
    },
    "outputs": [
@@ -2124,10 +2155,10 @@
    "id": "961c9128",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.454906Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.454582Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.464023Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.463522Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.543839Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.543752Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.551040Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.550770Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2256,10 +2287,10 @@
    "id": "4886f9e9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.466225Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.466081Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.472696Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.472188Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.552596Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.552485Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.557775Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.557510Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2289,10 +2320,10 @@
    "id": "b54d2da1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.475003Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.474857Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.488206Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.487746Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.559401Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.559315Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.570264Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.570004Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2397,10 +2428,10 @@
    "id": "1b71633a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.490521Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.490379Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.504489Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.504059Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.571718Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.571635Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.583621Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.583342Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2515,10 +2546,10 @@
    "id": "6d30a306",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.506891Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.506725Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.513731Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.513303Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.585282Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.585169Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.591106Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.590768Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2625,10 +2656,10 @@
    "id": "9a5ec13f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.516035Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.515894Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.640835Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.640080Z"
+     "iopub.execute_input": "2023-08-06T17:34:47.592639Z",
+     "iopub.status.busy": "2023-08-06T17:34:47.592536Z",
+     "iopub.status.idle": "2023-08-06T17:34:47.692002Z",
+     "shell.execute_reply": "2023-08-06T17:34:47.691684Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2636,7 +2667,7 @@
     {
      "data": {
       "text/plain": [
-       ""
+       ""
       ]
      },
      "execution_count": 34,
@@ -2691,10 +2722,10 @@
    "id": "09bbc0c6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.643135Z",
-     "iopub.status.busy": "2023-07-26T05:16:50.643008Z",
-     "iopub.status.idle": "2023-07-26T05:16:50.649451Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.649047Z"
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@@ -2742,10 +2773,10 @@
    "id": "2e1da1fa",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:50.651966Z",
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-     "iopub.status.idle": "2023-07-26T05:16:50.678716Z",
-     "shell.execute_reply": "2023-07-26T05:16:50.678209Z"
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     },
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    },
@@ -2950,7 +2981,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/Ch4-classification-lab.ipynb b/Ch4-classification-lab.ipynb
index 707e376..d9a9c90 100644
--- a/Ch4-classification-lab.ipynb
+++ b/Ch4-classification-lab.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e6cc127e",
+   "id": "cb3c07d1",
    "metadata": {},
    "source": [
     "\n",
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "af3093e5",
+   "id": "daef3e2e",
    "metadata": {},
    "source": [
     "# Lab: Logistic Regression, LDA, QDA, and KNN\n"
@@ -21,7 +21,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a4e58fe1",
+   "id": "3cb93478",
    "metadata": {},
    "source": [
     "## The Stock Market Data\n",
@@ -43,13 +43,13 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "71523a7f",
+   "id": "7b8d78b9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:52.147230Z",
-     "iopub.status.busy": "2023-07-26T05:16:52.147074Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.319384Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.318779Z"
+     "iopub.execute_input": "2023-08-06T17:34:48.984438Z",
+     "iopub.status.busy": "2023-08-06T17:34:48.984147Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.014450Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.013816Z"
     }
    },
    "outputs": [],
@@ -65,7 +65,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4759a767",
+   "id": "f420141c",
    "metadata": {},
    "source": [
     "We also collect together the new imports needed for this lab."
@@ -74,13 +74,13 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "901ed7c5",
+   "id": "b5938862",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.322482Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.322239Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.343077Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.342596Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.016761Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.016466Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.037738Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.037473Z"
     },
     "lines_to_next_cell": 2
    },
@@ -100,7 +100,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dd5a4d61",
+   "id": "34413b1c",
    "metadata": {},
    "source": [
     "Now we are ready to load the `Smarket` data."
@@ -109,13 +109,13 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "8b56ee0f",
+   "id": "e9fdf040",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.345526Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.345383Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.358625Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.357838Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.039423Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.039307Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.052006Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.051756Z"
     },
     "lines_to_next_cell": 0
    },
@@ -319,7 +319,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "400eb0f9",
+   "id": "d3533960",
    "metadata": {},
    "source": [
     "This gives a truncated listing of the data.\n",
@@ -329,13 +329,13 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "62d49b47",
+   "id": "69d5cfae",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.361002Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.360735Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.364261Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.363501Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.053494Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.053400Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.055808Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.055549Z"
     },
     "lines_to_next_cell": 0
    },
@@ -359,27 +359,27 @@
   },
   {
    "cell_type": "markdown",
-   "id": "82e38285",
+   "id": "c1e0cc8c",
    "metadata": {},
    "source": [
     "We compute the correlation matrix using the `corr()` method\n",
     "for data frames, which produces a matrix that contains all of\n",
     "the pairwise correlations among the variables.\n",
     " \n",
-    "The `pandas` library does not report a correlation for the `Direction`  variable because it is\n",
-    "qualitative."
+    "By instructing `pandas` to use only numeric variables, the `corr()` method does not report a correlation for the `Direction`  variable because it is\n",
+    " qualitative."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "bc34e7b7",
+   "id": "a4c0648e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.366253Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.366125Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.372926Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.372328Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.057221Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.057127Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.061952Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.061721Z"
     },
     "lines_to_next_cell": 0
    },
@@ -536,12 +536,12 @@
     }
    ],
    "source": [
-    "Smarket.corr()\n"
+    "Smarket.corr(numeric_only=True)\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "53a52be5",
+   "id": "c68bb37a",
    "metadata": {},
    "source": [
     "As one would expect, the correlations between the lagged return  variables and\n",
@@ -554,13 +554,13 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "9f075144",
+   "id": "cd40274b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.376785Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.376551Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.491023Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.490615Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.063425Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.063336Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.183910Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.181946Z"
     },
     "lines_to_next_cell": 2
    },
@@ -582,7 +582,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b8428c9e",
+   "id": "685b96e8",
    "metadata": {},
    "source": [
     "## Logistic Regression\n",
@@ -601,13 +601,13 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "2ab15aa3",
+   "id": "35b8bffe",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.493500Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.493302Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.566736Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.566181Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.187799Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.187442Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.293260Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.292298Z"
     },
     "lines_to_next_cell": 0
    },
@@ -723,7 +723,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ce1f682c",
+   "id": "68cca865",
    "metadata": {},
    "source": [
     "The smallest *p*-value here is associated with  `Lag1`. The\n",
@@ -741,13 +741,13 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "0faa6a6c",
+   "id": "4f9c5324",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.569154Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.568975Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.572426Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.572078Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.297671Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.297156Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.305507Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.303828Z"
     },
     "lines_to_next_cell": 0
    },
@@ -776,7 +776,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b989df1d",
+   "id": "681ca0cb",
    "metadata": {},
    "source": [
     "Likewise we can use the\n",
@@ -786,13 +786,13 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "108aff98",
+   "id": "75e44d01",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.574612Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.574492Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.578308Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.577846Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.309998Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.309526Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.317199Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.316460Z"
     }
    },
    "outputs": [
@@ -820,7 +820,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5c5c1f8e",
+   "id": "d4fd87bf",
    "metadata": {},
    "source": [
     "The `predict()`  method of `results` can be used to predict the\n",
@@ -837,13 +837,13 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "54b4b96c",
+   "id": "40164af5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.580578Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.580429Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.583750Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.583333Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.321143Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.320696Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.328214Z",
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@@ -867,7 +867,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b8f3c42",
+   "id": "94607ba9",
    "metadata": {},
    "source": [
     "In order to make a prediction as to whether the market will go up or\n",
@@ -881,13 +881,13 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "46c2887c",
+   "id": "daf20de2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.586085Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.585953Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.588706Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.588288Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.332514Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.332173Z",
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    },
@@ -899,7 +899,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "47ac8c81",
+   "id": "085aead4",
    "metadata": {},
    "source": [
     "The `confusion_table()`\n",
@@ -914,13 +914,13 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "0f816c4d",
+   "id": "71f4a40c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.590957Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.590766Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.598268Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.597798Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.342435Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.342079Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.354901Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.354601Z"
     }
    },
    "outputs": [
@@ -987,7 +987,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "327a9525",
+   "id": "3a338f26",
    "metadata": {},
    "source": [
     "The diagonal elements of the confusion matrix indicate correct\n",
@@ -1003,13 +1003,13 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "23668517",
+   "id": "78b2946b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.600706Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.600511Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.603872Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.603421Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.356729Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.356597Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.359259Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.359007Z"
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@@ -1031,7 +1031,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b1e8bf1",
+   "id": "54962226",
    "metadata": {},
    "source": [
     "\n"
@@ -1039,7 +1039,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1143b9c3",
+   "id": "aa9be981",
    "metadata": {},
    "source": [
     "At first glance, it appears that the logistic regression model is\n",
@@ -1066,13 +1066,13 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "86a02d7c",
+   "id": "e8a4d12e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.606055Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.605931Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.609917Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.609576Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.360879Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.360770Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.363453Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.363204Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1097,7 +1097,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "26b3a6d2",
+   "id": "946fac68",
    "metadata": {},
    "source": [
     "The object `train` is a vector of 1,250 elements, corresponding\n",
@@ -1132,13 +1132,13 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "f23b1c7b",
+   "id": "fd16bc2c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.612185Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.612009Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.618057Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.617645Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.364912Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.364808Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.369741Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.369422Z"
     }
    },
    "outputs": [],
@@ -1154,7 +1154,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ebe1900",
+   "id": "12382c18",
    "metadata": {},
    "source": [
     "Notice that we have trained and tested our model on two completely\n",
@@ -1169,13 +1169,13 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "82f849b9",
+   "id": "aaa9d07c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.620635Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.620266Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.623107Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.622634Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.371195Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.371114Z",
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@@ -1187,7 +1187,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ac89c253",
+   "id": "cc0d0c3a",
    "metadata": {},
    "source": [
     "Now we threshold the\n",
@@ -1198,13 +1198,13 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "e216583a",
+   "id": "5f0b3282",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.625601Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.625081Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.631930Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.631398Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.374386Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.374307Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.378599Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.378366Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1274,7 +1274,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f43e1451",
+   "id": "71ca598e",
    "metadata": {},
    "source": [
     "The test accuracy is about 48% while the error rate is about 52%"
@@ -1283,13 +1283,13 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "5538dc17",
+   "id": "7f4e49c0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.634500Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.634318Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.638177Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.637615Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.380021Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.379944Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.382451Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.382198Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1311,7 +1311,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3ddf7670",
+   "id": "96d75735",
    "metadata": {},
    "source": [
     "The `!=` notation means *not equal to*, and so the last command\n",
@@ -1341,13 +1341,13 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "016110f9",
+   "id": "9f94de4b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.640626Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.640465Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.650498Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.649952Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.383801Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.383724Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.391808Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.391549Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1425,7 +1425,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a7468a74",
+   "id": "1dd9ce3d",
    "metadata": {},
    "source": [
     "Let’s evaluate the overall accuracy as well as the accuracy within the days when\n",
@@ -1435,13 +1435,13 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "70984cd6",
+   "id": "69a4dd6b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.653494Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.652768Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.656801Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.656039Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.393244Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.393158Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.395426Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.395177Z"
     }
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@@ -1462,7 +1462,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "393c0a26",
+   "id": "14cf6b55",
    "metadata": {},
    "source": [
     "Now the results appear to be a little better: 56% of the daily\n",
@@ -1489,13 +1489,13 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "4b745fd8",
+   "id": "975fa3ca",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.659702Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.659530Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.664523Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.664140Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.396775Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.396693Z",
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@@ -1522,7 +1522,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ae928a3e",
+   "id": "bdc2c0bb",
    "metadata": {},
    "source": [
     "## Linear Discriminant Analysis"
@@ -1530,7 +1530,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "aab265c4",
+   "id": "41deab79",
    "metadata": {},
    "source": [
     "We begin by performing LDA on the  `Smarket`  data, using the function\n",
@@ -1541,13 +1541,13 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "cd533313",
+   "id": "7237ffa7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.668435Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.668202Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.670675Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.670317Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.401581Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.401504Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.403256Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.403010Z"
     }
    },
    "outputs": [],
@@ -1557,7 +1557,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c84aa056",
+   "id": "7289db40",
    "metadata": {},
    "source": [
     "Since the `LDA` estimator automatically \n",
@@ -1569,13 +1569,13 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "953dc6ac",
+   "id": "43a850eb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.673288Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.673119Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.681150Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.680147Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.404657Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.404587Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.414595Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.414353Z"
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     "lines_to_next_cell": 0
    },
@@ -1583,7 +1583,7 @@
     {
      "data": {
       "text/html": [
-       "
LinearDiscriminantAnalysis(store_covariance=True)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
+       "
LinearDiscriminantAnalysis(store_covariance=True)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
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        "LinearDiscriminantAnalysis(store_covariance=True)"
@@ -1602,7 +1602,7 @@
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   {
    "cell_type": "markdown",
-   "id": "0a51b5cd",
+   "id": "d3e0901f",
    "metadata": {},
    "source": [
     "Here we have used the list comprehensions introduced\n",
@@ -1625,13 +1625,13 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "8917085e",
+   "id": "86b6cece",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.683917Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.683495Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.686711Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.686302Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.416057Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.415959Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.418098Z",
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@@ -1654,7 +1654,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "14bc4692",
+   "id": "6d75a932",
    "metadata": {},
    "source": [
     "The estimated prior probabilities are stored in the `priors_` attribute.\n",
@@ -1666,13 +1666,13 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "efb3e9bd",
+   "id": "9362c7c6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.689572Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.689426Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.693007Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.692236Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.419417Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.419327Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.421334Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.421085Z"
     },
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    },
@@ -1694,7 +1694,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "50697f11",
+   "id": "61f77e19",
    "metadata": {},
    "source": [
     "The LDA output indicates that $\\hat\\pi_{Down}=0.492$ and\n",
@@ -1704,13 +1704,13 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "efce91fb",
+   "id": "e59858dc",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.698435Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.698251Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.701054Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.700738Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.422583Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.422510Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.424567Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.424332Z"
     },
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    },
@@ -1732,7 +1732,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a27bc841",
+   "id": "43a8fde1",
    "metadata": {},
    "source": [
     "The linear discriminant vectors can be found in the `scalings_` attribute:"
@@ -1741,13 +1741,13 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "e33cd6c5",
+   "id": "9b5f74e8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.703175Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.702968Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.706047Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.705603Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.425939Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.425863Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.427943Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.427700Z"
     }
    },
    "outputs": [
@@ -1769,7 +1769,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b011d741",
+   "id": "4655809e",
    "metadata": {},
    "source": [
     "These values provide the linear combination of `Lag1`  and `Lag2`  that are used to form the LDA decision rule. In other words, these are the multipliers of the elements of $X=x$ in (4.24).\n",
@@ -1779,13 +1779,13 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "dc8a5178",
+   "id": "fd8e6794",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.708404Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.708240Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.711274Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.710854Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.429283Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.429207Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.431271Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.431030Z"
     }
    },
    "outputs": [],
@@ -1795,7 +1795,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3c8a8a75",
+   "id": "2d211f0a",
    "metadata": {},
    "source": [
     "As we observed in our comparison of classification methods\n",
@@ -1806,13 +1806,13 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "31a6782b",
+   "id": "3bb63fb1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.713574Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.713379Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.718661Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.718207Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.432644Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.432568Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.436354Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.436113Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1880,26 +1880,26 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c3534a8f",
+   "id": "8e31152b",
    "metadata": {},
    "source": [
     "We can also estimate the\n",
     "probability of each class for\n",
     "each point in a training set. Applying a 50% threshold to the posterior probabilities of\n",
-    "being in class 1 allows us to\n",
+    "being in class one allows us to\n",
     "recreate the predictions contained in `lda_pred`."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "da1bffa3",
+   "id": "2b91f491",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.720875Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.720726Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.724610Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.724076Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.437709Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.437628Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.440441Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.440196Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1924,7 +1924,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ab71d7c",
+   "id": "d3a76822",
    "metadata": {},
    "source": [
     "Above, we used the `np.where()`  function that\n",
@@ -1937,13 +1937,13 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "3d7eae3c",
+   "id": "3a085714",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.726893Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.726728Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.730223Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.729787Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.441897Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.441821Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.444090Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.443865Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1967,7 +1967,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6a67baf1",
+   "id": "0aa9cbb3",
    "metadata": {},
    "source": [
     "If we wanted to use a posterior probability threshold other than\n",
@@ -1983,13 +1983,13 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "18fa175c",
+   "id": "345fb8c6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.732568Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.732400Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.735369Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.734923Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.445520Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.445423Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.447522Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.447281Z"
     }
    },
    "outputs": [
@@ -2010,7 +2010,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "527be6fe",
+   "id": "6798146c",
    "metadata": {},
    "source": [
     "No days in 2005 meet that threshold! In fact, the greatest posterior\n",
@@ -2034,7 +2034,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "66ecd10f",
+   "id": "58f2984f",
    "metadata": {},
    "source": [
     "## Quadratic Discriminant Analysis\n",
@@ -2048,20 +2048,20 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "62499aad",
+   "id": "22c6c2a3",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.737641Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.737376Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.742371Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.741972Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.448942Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.448849Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.452411Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.452173Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "
QuadraticDiscriminantAnalysis(store_covariance=True)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
+       "
QuadraticDiscriminantAnalysis(store_covariance=True)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
       ],
       "text/plain": [
        "QuadraticDiscriminantAnalysis(store_covariance=True)"
@@ -2079,7 +2079,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "17b38989",
+   "id": "fba0bb3a",
    "metadata": {},
    "source": [
     "The `QDA()` function will again compute `means_` and `priors_`."
@@ -2088,13 +2088,13 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "296fdd89",
+   "id": "992a790a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.744511Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.744359Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.747331Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.746954Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.453767Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.453689Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.455832Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.455573Z"
     }
    },
    "outputs": [
@@ -2117,7 +2117,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f439efa9",
+   "id": "8bc030e2",
    "metadata": {},
    "source": [
     "The `QDA()` classifier will estimate one covariance per class. Here is the\n",
@@ -2127,13 +2127,13 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "id": "7fbbefb0",
+   "id": "074c9d46",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.749983Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.749838Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.753016Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.752436Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.457173Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.457102Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.459117Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.458865Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2156,7 +2156,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4b33a370",
+   "id": "fa5963f6",
    "metadata": {},
    "source": [
     "The output contains the group means. But it does not contain the\n",
@@ -2169,13 +2169,13 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "id": "03094dcd",
+   "id": "3c95aae1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.754995Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.754855Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.760423Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.760086Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.460495Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.460408Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.464611Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.464381Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2244,7 +2244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2037df4b",
+   "id": "0a72c1b8",
    "metadata": {},
    "source": [
     "Interestingly, the QDA predictions are accurate almost 60% of the\n",
@@ -2254,13 +2254,13 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "id": "25022d1a",
+   "id": "935b2079",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.762503Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.762361Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.765264Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.764918Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.466057Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.465982Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.468265Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.468008Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2282,7 +2282,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cf85b45e",
+   "id": "cbf4d7d1",
    "metadata": {},
    "source": [
     "This level of accuracy is quite impressive for stock market data, which is\n",
@@ -2296,7 +2296,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "258f98b8",
+   "id": "b89dfb88",
    "metadata": {},
    "source": [
     "## Naive Bayes\n",
@@ -2310,13 +2310,13 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "id": "f73eb202",
+   "id": "628b0355",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.767345Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.767204Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.771774Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.771427Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.469713Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.469632Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.473211Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.472970Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2324,7 +2324,7 @@
     {
      "data": {
       "text/html": [
-       "
GaussianNB()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
+       "
GaussianNB()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
       ],
       "text/plain": [
        "GaussianNB()"
@@ -2342,7 +2342,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9911dcdc",
+   "id": "66916c68",
    "metadata": {},
    "source": [
     "The classes are stored as `classes_`."
@@ -2351,13 +2351,13 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "id": "8e860cc3",
+   "id": "8a5fc302",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.773771Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.773609Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.776397Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.776019Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.474613Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.474532Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.476603Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.476363Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2379,7 +2379,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8d6b9b33",
+   "id": "753c7d37",
    "metadata": {},
    "source": [
     "The class prior probabilities are stored in the `class_prior_` attribute."
@@ -2388,13 +2388,13 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "id": "c28bf3b5",
+   "id": "6b1b5cc6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.778509Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.778344Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.781156Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.780778Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.477928Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.477856Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.479875Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.479628Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2416,7 +2416,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fed2c4b4",
+   "id": "848e5d7c",
    "metadata": {},
    "source": [
     "The parameters of the features can be found in the `theta_` and `var_` attributes. The number of rows\n",
@@ -2427,13 +2427,13 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "id": "84a9f086",
+   "id": "1a4b7cb0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.783409Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.783220Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.786972Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.786412Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.481268Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.481197Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.483169Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.482928Z"
     }
    },
    "outputs": [
@@ -2455,7 +2455,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "66f0a08d",
+   "id": "60efd24c",
    "metadata": {},
    "source": [
     "Its variance is 1.503."
@@ -2464,13 +2464,13 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "id": "885f5165",
+   "id": "f59d7cb4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.789289Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.789145Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.792294Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.791863Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.484569Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.484500Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.486506Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.486244Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2493,10 +2493,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "db0a1ce6",
+   "id": "4518d5db",
    "metadata": {},
    "source": [
-    "How do we know the names of these attributes? We use `NB?` (or \\textR?NB}).\n",
+    "How do we know the names of these attributes? We use `NB?` (or `?NB`).\n",
     "\n",
     "We can easily verify the mean computation:"
    ]
@@ -2504,13 +2504,13 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "id": "61473094",
+   "id": "aa50d0b8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.794766Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.794585Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.798951Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.798539Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.487873Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.487800Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.490700Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.490454Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2534,7 +2534,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d4ffc86b",
+   "id": "3ee8e214",
    "metadata": {},
    "source": [
     "Similarly for the variance:"
@@ -2543,13 +2543,13 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "id": "db203a23",
+   "id": "3a2b0653",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.801373Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.801183Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.805590Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.805195Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.492036Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.491958Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.494698Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.494456Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2573,7 +2573,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7c9078c1",
+   "id": "5cb3b59d",
    "metadata": {},
    "source": [
     "Since `NB()` is a classifier in the `sklearn` library, making predictions\n",
@@ -2583,13 +2583,13 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "id": "b387227e",
+   "id": "938f09ea",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.808068Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.807902Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.813920Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.813575Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.496066Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.495993Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.500129Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.499891Z"
     }
    },
    "outputs": [
@@ -2657,7 +2657,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ab979471",
+   "id": "a0ce38d6",
    "metadata": {},
    "source": [
     "Naive Bayes performs well on these data, with accurate predictions over 59% of the time. This is slightly worse than QDA, but much better than LDA.\n",
@@ -2668,13 +2668,13 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "id": "f14ebe61",
+   "id": "42f0e4a2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.816106Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.815946Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.819614Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.819281Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.501537Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.501460Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.505359Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.505091Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2700,7 +2700,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f14c520d",
+   "id": "ede194da",
    "metadata": {},
    "source": [
     "## K-Nearest Neighbors\n",
@@ -2718,13 +2718,13 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "id": "41a12f4a",
+   "id": "8b833ee4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.821819Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.821654Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.835418Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.834963Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.506696Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.506614Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.517822Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.517573Z"
     }
    },
    "outputs": [
@@ -2787,6 +2787,7 @@
    ],
    "source": [
     "knn1 = KNeighborsClassifier(n_neighbors=1)\n",
+    "X_train, X_test = [np.asarray(X) for X in [X_train, X_test]]\n",
     "knn1.fit(X_train, L_train)\n",
     "knn1_pred = knn1.predict(X_test)\n",
     "confusion_table(knn1_pred, L_test)\n"
@@ -2794,7 +2795,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "22ee6dff",
+   "id": "5fb57a8d",
    "metadata": {},
    "source": [
     "The results using $K=1$ are not very good, since only $50%$ of the\n",
@@ -2805,13 +2806,13 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "id": "1dd2f3e4",
+   "id": "45410b7f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.840858Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.840380Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.844994Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.844563Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.519187Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.519097Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.521354Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.521132Z"
     }
    },
    "outputs": [
@@ -2832,23 +2833,23 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cda2465d",
+   "id": "500e00a1",
    "metadata": {},
    "source": [
-    "Below, we repeat the\n",
-    "analysis using $K=3$."
+    "We repeat the\n",
+    "analysis below using $K=3$."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 49,
-   "id": "8ec72efc",
+   "id": "ae6e0156",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.848486Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.848323Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.859379Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.859009Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.522772Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.522694Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.530247Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.530016Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2872,7 +2873,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ff4533bd",
+   "id": "11a369af",
    "metadata": {},
    "source": [
     "The results have improved slightly. But increasing *K* further\n",
@@ -2883,7 +2884,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5810022d",
+   "id": "ab3b1e64",
    "metadata": {},
    "source": [
     "KNN does not perform well on the `Smarket`  data, but it often does provide impressive results. As an example we will apply the KNN approach to the `Caravan`  data set, which is part of the `ISLP` library.  This data set includes 85\n",
@@ -2897,13 +2898,13 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "id": "98fef4ed",
+   "id": "9338564d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.862002Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.861826Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.880744Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.880217Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.531745Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.531662Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.550259Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.549964Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2929,25 +2930,25 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4fc1a1df",
+   "id": "ba5e14a9",
    "metadata": {},
    "source": [
     "The method `value_counts()` takes a `pd.Series` or `pd.DataFrame` and returns\n",
     "a `pd.Series` with the corresponding counts\n",
     "for each unique element. In this case `Purchase` has only `Yes` and `No` values\n",
-    "and returns how many values of each there are."
+    "and the method returns how many values of each there are."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 51,
-   "id": "1af72c0b",
+   "id": "a94f2ea7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.883491Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.883258Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.886241Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.885825Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.551792Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.551695Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.553719Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.553499Z"
     },
     "lines_to_next_cell": 2
    },
@@ -2969,7 +2970,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "78c25fda",
+   "id": "a753d948",
    "metadata": {},
    "source": [
     "Our features will include all columns except `Purchase`."
@@ -2978,13 +2979,13 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "id": "9ea841e4",
+   "id": "6b6438b0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.888642Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.888457Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.891757Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.891278Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.555038Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.554947Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.557311Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.557082Z"
     }
    },
    "outputs": [],
@@ -2994,7 +2995,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "55efb306",
+   "id": "52a62ab9",
    "metadata": {},
    "source": [
     "Because the KNN classifier predicts the class of a given test\n",
@@ -3027,13 +3028,13 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "id": "6e26b14f",
+   "id": "158bfb3f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.893952Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.893809Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.896350Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.895913Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.558624Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.558538Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.560136Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.559910Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3046,7 +3047,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c0d1faf",
+   "id": "45baf26c",
    "metadata": {},
    "source": [
     "The argument `with_mean` indicates whether or not\n",
@@ -3066,13 +3067,13 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "id": "bd178f38",
+   "id": "d11b04c4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.898581Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.898422Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.907100Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.906252Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.561466Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.561387Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.567529Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.567268Z"
     },
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    },
@@ -3084,7 +3085,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "30bfaa05",
+   "id": "f388fe5b",
    "metadata": {},
    "source": [
     "Now every column of `feature_std` below has a standard deviation of\n",
@@ -3094,13 +3095,13 @@
   {
    "cell_type": "code",
    "execution_count": 55,
-   "id": "18929b37",
+   "id": "f0c65b34",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.909697Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.909376Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.917328Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.916861Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.569138Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.569036Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.577122Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.576863Z"
     }
    },
    "outputs": [
@@ -3135,10 +3136,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4f536808",
+   "id": "9668a83b",
    "metadata": {},
    "source": [
-    "Notice that the standard deviations are not quite $1$ here; this is again due to some procedures using the $1/n$ convention for variances (in this case `scaler()`), while others use $1/(n-1)$ (the `std()` method). See the footnote on page 198.\n",
+    "Notice that the standard deviations are not quite $1$ here; this is again due to some procedures using the $1/n$ convention for variances (in this case `scaler()`), while others use $1/(n-1)$ (the `std()` method). See the footnote on page 103.\n",
     "In this case it does not matter, as long as the variables are all on the same scale.\n",
     "\n",
     "Using the function `train_test_split()`  we now split the observations into a test set,\n",
@@ -3150,13 +3151,13 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "id": "9d439d0b",
+   "id": "3861cc4f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.919758Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.919493Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.924297Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.923909Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.578604Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.578502Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.582699Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.582426Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3165,7 +3166,7 @@
     "(X_train,\n",
     " X_test,\n",
     " y_train,\n",
-    " y_test) = train_test_split(feature_std,\n",
+    " y_test) = train_test_split(np.asarray(feature_std),\n",
     "                            Purchase,\n",
     "                            test_size=1000,\n",
     "                            random_state=0)\n"
@@ -3173,10 +3174,11 @@
   },
   {
    "cell_type": "markdown",
-   "id": "87fcf773",
+   "id": "3cd24d0a",
    "metadata": {},
    "source": [
-    "`?train_test_split` reveals that the non-keyword arguments can be `lists`, `arrays`, `pandas dataframes` etc that all have the same length (`shape[0]`) and hence are *indexable*. In this case they are the dataframe `feature_std` and the response variable `Purchase`. \n",
+    "`?train_test_split` reveals that the non-keyword arguments can be `lists`, `arrays`, `pandas dataframes` etc that all have the same length (`shape[0]`) and hence are *indexable*. In this case they are the dataframe `feature_std` and the response variable `Purchase`.\n",
+    " {Note that we have converted `feature_std` to an `ndarray` to address a bug in `sklearn`.}\n",
     "We fit a KNN model on the training data using $K=1$,\n",
     "and evaluate its performance on the test data."
    ]
@@ -3184,13 +3186,13 @@
   {
    "cell_type": "code",
    "execution_count": 57,
-   "id": "9b8c0171",
+   "id": "1b9d7b32",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.926683Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.926533Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.979689Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.979266Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.584364Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.584256Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.908198Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.907710Z"
     },
     "lines_to_next_cell": 2
    },
@@ -3214,7 +3216,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3aa030b6",
+   "id": "0464c302",
    "metadata": {},
    "source": [
     "The KNN error rate on the 1,000 test observations is about $11%$.\n",
@@ -3237,13 +3239,13 @@
   {
    "cell_type": "code",
    "execution_count": 58,
-   "id": "f31b6e26",
+   "id": "d683b2f9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.982811Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.982601Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.989512Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.989071Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.910374Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.910235Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.916751Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.916357Z"
     }
    },
    "outputs": [
@@ -3310,7 +3312,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "de5fb529",
+   "id": "19ed36b1",
    "metadata": {},
    "source": [
     "It turns out that KNN with $K=1$ does far better than random guessing\n",
@@ -3322,13 +3324,13 @@
   {
    "cell_type": "code",
    "execution_count": 59,
-   "id": "4a8c37aa",
+   "id": "3498856a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.992418Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.992103Z",
-     "iopub.status.idle": "2023-07-26T05:16:53.995535Z",
-     "shell.execute_reply": "2023-07-26T05:16:53.995078Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.918891Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.918771Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.921176Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.920892Z"
     },
     "lines_to_next_cell": 2
    },
@@ -3350,7 +3352,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a898b7d0",
+   "id": "3ec215b9",
    "metadata": {},
    "source": [
     "### Tuning Parameters\n",
@@ -3366,13 +3368,13 @@
   {
    "cell_type": "code",
    "execution_count": 60,
-   "id": "153662f8",
+   "id": "9ed36c50",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:53.999510Z",
-     "iopub.status.busy": "2023-07-26T05:16:53.999082Z",
-     "iopub.status.idle": "2023-07-26T05:16:54.130823Z",
-     "shell.execute_reply": "2023-07-26T05:16:54.130318Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.923079Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.922965Z",
+     "iopub.status.idle": "2023-08-06T17:34:50.996569Z",
+     "shell.execute_reply": "2023-08-06T17:34:50.996126Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3407,7 +3409,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "39ba18b3",
+   "id": "0718d8f0",
    "metadata": {},
    "source": [
     "We see some variability ---  the numbers for `K=4` are very different from the rest.\n",
@@ -3433,13 +3435,13 @@
   {
    "cell_type": "code",
    "execution_count": 61,
-   "id": "55b99a3f",
+   "id": "8605a327",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:54.134280Z",
-     "iopub.status.busy": "2023-07-26T05:16:54.133924Z",
-     "iopub.status.idle": "2023-07-26T05:16:54.790553Z",
-     "shell.execute_reply": "2023-07-26T05:16:54.788632Z"
+     "iopub.execute_input": "2023-08-06T17:34:50.998620Z",
+     "iopub.status.busy": "2023-08-06T17:34:50.998492Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.629504Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.628869Z"
     }
    },
    "outputs": [
@@ -3476,12 +3478,12 @@
        "  \n",
        "    \n",
        "      No\n",
-       "      933\n",
+       "      931\n",
        "      67\n",
        "    \n",
        "    \n",
        "      Yes\n",
-       "      0\n",
+       "      2\n",
        "      0\n",
        "    \n",
        "  \n",
@@ -3491,8 +3493,8 @@
       "text/plain": [
        "Truth       No  Yes\n",
        "Predicted          \n",
-       "No         933   67\n",
-       "Yes          0    0"
+       "No         931   67\n",
+       "Yes          2    0"
       ]
      },
      "execution_count": 61,
@@ -3504,13 +3506,13 @@
     "logit = LogisticRegression(C=1e10, solver='liblinear')\n",
     "logit.fit(X_train, y_train)\n",
     "logit_pred = logit.predict_proba(X_test)\n",
-    "logit_labels = np.where(logit_pred[:,1] > 5, 'Yes', 'No')\n",
+    "logit_labels = np.where(logit_pred[:,1] > .5, 'Yes', 'No')\n",
     "confusion_table(logit_labels, y_test)\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "4e0ebc83",
+   "id": "daf1655f",
    "metadata": {},
    "source": [
     "We used the argument `solver='liblinear'` above to\n",
@@ -3518,8 +3520,8 @@
     "the algorithm does not converge.\n",
     "\n",
     "If we use $0.5$ as the predicted probability cut-off for the\n",
-    "classifier, then we have a problem: none of the test\n",
-    "observations are predicted to purchase insurance.  However, we are not required to use a\n",
+    "classifier, then we have a problem: only two of the test observations\n",
+    "are predicted to purchase insurance.  However, we are not required to use a\n",
     "cut-off of $0.5$. If we instead predict a purchase any time the\n",
     "predicted probability of purchase exceeds $0.25$, we get much better\n",
     "results: we predict that 29 people will purchase insurance, and we are\n",
@@ -3530,13 +3532,13 @@
   {
    "cell_type": "code",
    "execution_count": 62,
-   "id": "0c2ea9f5",
+   "id": "e686f675",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:54.800869Z",
-     "iopub.status.busy": "2023-07-26T05:16:54.800067Z",
-     "iopub.status.idle": "2023-07-26T05:16:54.901396Z",
-     "shell.execute_reply": "2023-07-26T05:16:54.824967Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.634589Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.634253Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.649626Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.648919Z"
     }
    },
    "outputs": [
@@ -3605,13 +3607,13 @@
   {
    "cell_type": "code",
    "execution_count": 63,
-   "id": "3a6bf0a4",
+   "id": "d92cfcd4",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:55.014712Z",
-     "iopub.status.busy": "2023-07-26T05:16:55.014300Z",
-     "iopub.status.idle": "2023-07-26T05:16:55.022432Z",
-     "shell.execute_reply": "2023-07-26T05:16:55.021283Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.653353Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.653069Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.659794Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.658989Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3633,7 +3635,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4d04bbc7",
+   "id": "8a0c1140",
    "metadata": {},
    "source": [
     "## Linear and Poisson Regression on the Bikeshare Data\n",
@@ -3645,13 +3647,13 @@
   {
    "cell_type": "code",
    "execution_count": 64,
-   "id": "769300df",
+   "id": "6f93060c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:55.026479Z",
-     "iopub.status.busy": "2023-07-26T05:16:55.026122Z",
-     "iopub.status.idle": "2023-07-26T05:16:55.040298Z",
-     "shell.execute_reply": "2023-07-26T05:16:55.039107Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.664042Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.663443Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.685390Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.684689Z"
     },
     "lines_to_next_cell": 0
    },
@@ -3662,7 +3664,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8cc82fa9",
+   "id": "af82d61e",
    "metadata": {},
    "source": [
     "Let's have a peek at the dimensions and names of the variables in this dataframe."
@@ -3671,13 +3673,13 @@
   {
    "cell_type": "code",
    "execution_count": 65,
-   "id": "02b351f5",
+   "id": "725ce173",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:55.043729Z",
-     "iopub.status.busy": "2023-07-26T05:16:55.043547Z",
-     "iopub.status.idle": "2023-07-26T05:16:55.047018Z",
-     "shell.execute_reply": "2023-07-26T05:16:55.046428Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.689828Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.689209Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.696435Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.695780Z"
     }
    },
    "outputs": [
@@ -3702,7 +3704,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7784e3a1",
+   "id": "9b133dc3",
    "metadata": {},
    "source": [
     "### Linear Regression\n",
@@ -3713,13 +3715,13 @@
   {
    "cell_type": "code",
    "execution_count": 66,
-   "id": "926c908d",
+   "id": "ee3e5e3b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:55.049121Z",
-     "iopub.status.busy": "2023-07-26T05:16:55.049011Z",
-     "iopub.status.idle": "2023-07-26T05:16:55.569728Z",
-     "shell.execute_reply": "2023-07-26T05:16:55.567494Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.700999Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.700652Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.771460Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.770793Z"
     }
    },
    "outputs": [
@@ -4097,7 +4099,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b29a0708",
+   "id": "36f3063f",
    "metadata": {},
    "source": [
     "There are 24 levels in `hr` and 40 rows in all.\n",
@@ -4117,13 +4119,13 @@
   {
    "cell_type": "code",
    "execution_count": 67,
-   "id": "064b24d1",
+   "id": "d6a047f5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:55.575305Z",
-     "iopub.status.busy": "2023-07-26T05:16:55.575124Z",
-     "iopub.status.idle": "2023-07-26T05:16:55.582612Z",
-     "shell.execute_reply": "2023-07-26T05:16:55.580612Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.777342Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.777095Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.781327Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.780152Z"
     },
     "lines_to_next_cell": 0
    },
@@ -4135,7 +4137,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fba11e8e",
+   "id": "6ed435ca",
    "metadata": {},
    "source": [
     "Refitting again:"
@@ -4144,13 +4146,13 @@
   {
    "cell_type": "code",
    "execution_count": 68,
-   "id": "27c1aa54",
+   "id": "d7f6edaf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:55.591223Z",
-     "iopub.status.busy": "2023-07-26T05:16:55.589141Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.075120Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.073529Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.785799Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.785477Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.868170Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.867180Z"
     }
    },
    "outputs": [
@@ -4528,7 +4530,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d057b162",
+   "id": "edea9530",
    "metadata": {},
    "source": [
     "What is the difference between the two codings?  In `M2_lm`, a\n",
@@ -4554,20 +4556,20 @@
   {
    "cell_type": "code",
    "execution_count": 69,
-   "id": "dd0114c8",
+   "id": "412ce964",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.092324Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.087118Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.137844Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.135218Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.872605Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.872217Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.880273Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.879520Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "4.090076132857841e-19"
+       "4.186226544780569e-19"
       ]
      },
      "execution_count": 69,
@@ -4581,7 +4583,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bcb6ae87",
+   "id": "69539d1c",
    "metadata": {},
    "source": [
     "The sum of squared differences is zero. We can also see this using the\n",
@@ -4591,13 +4593,13 @@
   {
    "cell_type": "code",
    "execution_count": 70,
-   "id": "292585a1",
+   "id": "5afd0d5d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.147457Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.146798Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.159395Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.157990Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.885577Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.885206Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.893099Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.892367Z"
     },
     "lines_to_next_cell": 2
    },
@@ -4619,7 +4621,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5bffbdd1",
+   "id": "fdc83f2e",
    "metadata": {},
    "source": [
     "To reproduce the left-hand side of Figure 4.13\n",
@@ -4634,13 +4636,13 @@
   {
    "cell_type": "code",
    "execution_count": 71,
-   "id": "e05e0575",
+   "id": "4629f2c9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.169355Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.168352Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.190269Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.186463Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.896788Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.896443Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.903051Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.902328Z"
     },
     "lines_to_next_cell": 0
    },
@@ -4674,7 +4676,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d542caac",
+   "id": "6fdd5f23",
    "metadata": {},
    "source": [
     "Next, we append `Dec` as the negative of the sum of all other months."
@@ -4683,13 +4685,13 @@
   {
    "cell_type": "code",
    "execution_count": 72,
-   "id": "9f04a25e",
+   "id": "b3e55833",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.213429Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.210143Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.249114Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.246382Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.906797Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.906546Z",
+     "iopub.status.idle": "2023-08-06T17:34:51.914013Z",
+     "shell.execute_reply": "2023-08-06T17:34:51.913335Z"
     },
     "lines_to_next_cell": 0
    },
@@ -4730,7 +4732,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6e3ef375",
+   "id": "4d1f1d30",
    "metadata": {},
    "source": [
     "Finally, to make the plot neater, we’ll just use the first letter of each month, which is the $6$th entry of each of\n",
@@ -4740,13 +4742,13 @@
   {
    "cell_type": "code",
    "execution_count": 73,
-   "id": "20c7c054",
+   "id": "cdbebc03",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.310254Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.306244Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.486315Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.485755Z"
+     "iopub.execute_input": "2023-08-06T17:34:51.917669Z",
+     "iopub.status.busy": "2023-08-06T17:34:51.917450Z",
+     "iopub.status.idle": "2023-08-06T17:34:52.060250Z",
+     "shell.execute_reply": "2023-08-06T17:34:52.059542Z"
     }
    },
    "outputs": [
@@ -4773,7 +4775,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6032f6a9",
+   "id": "6f845be8",
    "metadata": {},
    "source": [
     "Reproducing the  right-hand plot in Figure 4.13  follows a similar process."
@@ -4782,13 +4784,13 @@
   {
    "cell_type": "code",
    "execution_count": 74,
-   "id": "3f83f4bf",
+   "id": "170fd6fd",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.489411Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.489143Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.493292Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.492665Z"
+     "iopub.execute_input": "2023-08-06T17:34:52.064472Z",
+     "iopub.status.busy": "2023-08-06T17:34:52.064205Z",
+     "iopub.status.idle": "2023-08-06T17:34:52.071346Z",
+     "shell.execute_reply": "2023-08-06T17:34:52.070685Z"
     }
    },
    "outputs": [],
@@ -4802,7 +4804,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "58200be9",
+   "id": "100190e3",
    "metadata": {},
    "source": [
     "We now make the hour plot."
@@ -4811,13 +4813,13 @@
   {
    "cell_type": "code",
    "execution_count": 75,
-   "id": "86e9a741",
+   "id": "1e09e126",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.496145Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.495966Z",
-     "iopub.status.idle": "2023-07-26T05:16:56.609790Z",
-     "shell.execute_reply": "2023-07-26T05:16:56.609280Z"
+     "iopub.execute_input": "2023-08-06T17:34:52.075772Z",
+     "iopub.status.busy": "2023-08-06T17:34:52.075406Z",
+     "iopub.status.idle": "2023-08-06T17:34:52.204803Z",
+     "shell.execute_reply": "2023-08-06T17:34:52.204415Z"
     }
    },
    "outputs": [
@@ -4844,7 +4846,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5db06a3e",
+   "id": "bf730e5d",
    "metadata": {},
    "source": [
     "### Poisson Regression\n",
@@ -4857,13 +4859,13 @@
   {
    "cell_type": "code",
    "execution_count": 76,
-   "id": "a9448278",
+   "id": "a6667dcf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:56.612317Z",
-     "iopub.status.busy": "2023-07-26T05:16:56.612179Z",
-     "iopub.status.idle": "2023-07-26T05:16:57.099663Z",
-     "shell.execute_reply": "2023-07-26T05:16:57.097888Z"
+     "iopub.execute_input": "2023-08-06T17:34:52.206616Z",
+     "iopub.status.busy": "2023-08-06T17:34:52.206494Z",
+     "iopub.status.idle": "2023-08-06T17:34:52.270836Z",
+     "shell.execute_reply": "2023-08-06T17:34:52.270019Z"
     }
    },
    "outputs": [],
@@ -4873,7 +4875,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e7b3bc38",
+   "id": "8309c1fc",
    "metadata": {},
    "source": [
     "We can plot the coefficients associated with `mnth` and `hr`, in order to reproduce  Figure 4.15. We first complete these coefficients as before."
@@ -4882,13 +4884,13 @@
   {
    "cell_type": "code",
    "execution_count": 77,
-   "id": "ec8505be",
+   "id": "c20de5d8",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:16:57.113476Z",
-     "iopub.status.busy": "2023-07-26T05:16:57.110476Z",
-     "iopub.status.idle": "2023-07-26T05:16:57.156419Z",
-     "shell.execute_reply": "2023-07-26T05:16:57.148075Z"
+     "iopub.execute_input": "2023-08-06T17:34:52.275471Z",
+     "iopub.status.busy": "2023-08-06T17:34:52.275064Z",
+     "iopub.status.idle": "2023-08-06T17:34:52.302707Z",
+     "shell.execute_reply": "2023-08-06T17:34:52.302018Z"
     },
     "lines_to_next_cell": 0
    },
@@ -4907,7 +4909,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f6fb37ef",
+   "id": "41e58943",
    "metadata": {},
    "source": [
     "The plotting is as before."
@@ -4916,13 +4918,13 @@
   {
    "cell_type": "code",
    "execution_count": 78,
-   "id": "0b8a5edf",
+   "id": "4a1a8488",
    "metadata": {
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-     "iopub.execute_input": "2023-07-26T05:16:57.169051Z",
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@@ -4931,7 +4933,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_69056/3779905754.py:8: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
+      "/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_84993/3779905754.py:8: UserWarning: FixedFormatter should only be used together with FixedLocator\n",
       "  ax_hr.set_xticklabels(range(24)[::2], fontsize=20)\n"
      ]
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@@ -4961,7 +4963,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3c256bf2",
+   "id": "5e74d13e",
    "metadata": {},
    "source": [
     "We compare the fitted values of the two models.\n",
@@ -4973,13 +4975,13 @@
   {
    "cell_type": "code",
    "execution_count": 79,
-   "id": "d487c7ed",
+   "id": "a3158334",
    "metadata": {
     "execution": {
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@@ -5007,7 +5009,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "17ccc1bf",
+   "id": "2b03ac4f",
    "metadata": {},
    "source": [
     "The predictions from the Poisson regression model are correlated with\n",
@@ -5032,6 +5034,11 @@
    "main_language": "python",
    "notebook_metadata_filter": "-all"
   },
+  "kernelspec": {
+   "display_name": "Python3 (islp_freeze_311)",
+   "language": "python",
+   "name": "islp_freeze_311"
+  },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
@@ -5042,7 +5049,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.4"
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diff --git a/Ch5-resample-lab.ipynb b/Ch5-resample-lab.ipynb
index 787ce82..950726d 100644
--- a/Ch5-resample-lab.ipynb
+++ b/Ch5-resample-lab.ipynb
@@ -29,10 +29,10 @@
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@@ -61,10 +61,10 @@
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@@ -105,10 +105,10 @@
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@@ -133,10 +133,10 @@
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@@ -163,10 +163,10 @@
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@@ -207,10 +207,10 @@
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@@ -250,10 +250,10 @@
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@@ -294,10 +294,10 @@
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@@ -377,10 +377,10 @@
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@@ -445,10 +445,10 @@
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@@ -502,10 +502,10 @@
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@@ -544,10 +544,10 @@
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@@ -609,10 +609,10 @@
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@@ -653,10 +653,10 @@
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@@ -727,10 +727,10 @@
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@@ -761,10 +761,10 @@
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@@ -800,10 +800,10 @@
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@@ -888,10 +888,10 @@
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@@ -954,10 +954,10 @@
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@@ -989,10 +989,10 @@
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@@ -1022,10 +1022,10 @@
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@@ -1073,10 +1073,10 @@
    "id": "14ce3afa",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:01.887739Z",
-     "iopub.status.busy": "2023-07-26T05:17:01.887564Z",
-     "iopub.status.idle": "2023-07-26T05:17:03.352633Z",
-     "shell.execute_reply": "2023-07-26T05:17:03.352273Z"
+     "iopub.execute_input": "2023-08-06T17:34:56.479382Z",
+     "iopub.status.busy": "2023-08-06T17:34:56.479299Z",
+     "iopub.status.idle": "2023-08-06T17:34:57.627980Z",
+     "shell.execute_reply": "2023-08-06T17:34:57.627706Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1123,10 +1123,10 @@
    "id": "6b1213ac",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:03.356355Z",
-     "iopub.status.busy": "2023-07-26T05:17:03.356184Z",
-     "iopub.status.idle": "2023-07-26T05:17:03.453023Z",
-     "shell.execute_reply": "2023-07-26T05:17:03.452622Z"
+     "iopub.execute_input": "2023-08-06T17:34:57.629628Z",
+     "iopub.status.busy": "2023-08-06T17:34:57.629520Z",
+     "iopub.status.idle": "2023-08-06T17:34:57.687018Z",
+     "shell.execute_reply": "2023-08-06T17:34:57.686748Z"
     },
     "lines_to_next_cell": 2
    },
@@ -1195,10 +1195,10 @@
    "id": "af99b778",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:03.455469Z",
-     "iopub.status.busy": "2023-07-26T05:17:03.455201Z",
-     "iopub.status.idle": "2023-07-26T05:17:05.757186Z",
-     "shell.execute_reply": "2023-07-26T05:17:05.756703Z"
+     "iopub.execute_input": "2023-08-06T17:34:57.688662Z",
+     "iopub.status.busy": "2023-08-06T17:34:57.688521Z",
+     "iopub.status.idle": "2023-08-06T17:34:59.481117Z",
+     "shell.execute_reply": "2023-08-06T17:34:59.480813Z"
     }
    },
    "outputs": [
@@ -1238,10 +1238,10 @@
    "id": "0206281e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:05.759524Z",
-     "iopub.status.busy": "2023-07-26T05:17:05.759220Z",
-     "iopub.status.idle": "2023-07-26T05:17:05.769493Z",
-     "shell.execute_reply": "2023-07-26T05:17:05.768995Z"
+     "iopub.execute_input": "2023-08-06T17:34:59.482760Z",
+     "iopub.status.busy": "2023-08-06T17:34:59.482640Z",
+     "iopub.status.idle": "2023-08-06T17:34:59.491295Z",
+     "shell.execute_reply": "2023-08-06T17:34:59.491041Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1292,7 +1292,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/Ch6-varselect-lab.ipynb b/Ch6-varselect-lab.ipynb
index c78185a..9850367 100644
--- a/Ch6-varselect-lab.ipynb
+++ b/Ch6-varselect-lab.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "1e9ee9d8",
+   "id": "73428d07",
    "metadata": {},
    "source": [
     "\n",
@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98c1f26d",
+   "id": "3479aab9",
    "metadata": {},
    "source": [
     "# Lab: Linear Models and Regularization Methods\n",
@@ -23,13 +23,13 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "564883b2",
+   "id": "a121caba",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:07.048830Z",
-     "iopub.status.busy": "2023-07-26T05:17:07.048718Z",
-     "iopub.status.idle": "2023-07-26T05:17:08.239907Z",
-     "shell.execute_reply": "2023-07-26T05:17:08.239413Z"
+     "iopub.execute_input": "2023-08-06T17:35:00.786819Z",
+     "iopub.status.busy": "2023-08-06T17:35:00.786401Z",
+     "iopub.status.idle": "2023-08-06T17:35:01.840861Z",
+     "shell.execute_reply": "2023-08-06T17:35:01.840276Z"
     }
    },
    "outputs": [],
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0594e13e",
+   "id": "b846a10e",
    "metadata": {},
    "source": [
     "We again collect the new imports\n",
@@ -58,13 +58,13 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "9aa8d3ee",
+   "id": "91b5adfb",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:08.242431Z",
-     "iopub.status.busy": "2023-07-26T05:17:08.242231Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.939443Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.938977Z"
+     "iopub.execute_input": "2023-08-06T17:35:01.843052Z",
+     "iopub.status.busy": "2023-08-06T17:35:01.842795Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.677217Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.676896Z"
     },
     "lines_to_next_cell": 0
    },
@@ -73,13 +73,11 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Requirement already satisfied: l0bnb in /Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages (1.0.0)\r\n",
-      "Requirement already satisfied: numpy>=1.18.1 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages (from l0bnb) (1.21.6)\r\n",
-      "Requirement already satisfied: scipy>=1.4.1 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages (from l0bnb) (1.10.1)\r\n",
-      "Requirement already satisfied: numba>=0.53.1 in /Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/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_39/lib/python3.9/site-packages (from numba>=0.53.1->l0bnb) (0.40.1)\r\n",
-      "\u001b[33mDEPRECATION: pytorch-lightning 1.7.7 has a non-standard dependency specifier torch>=1.9.*. pip 23.3 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\r\n",
-      "\u001b[0m"
+      "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"
      ]
     }
    ],
@@ -97,7 +95,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "06a58c0b",
+   "id": "d363de72",
    "metadata": {},
    "source": [
     "We have installed the package `l0bnb` on the fly. Note the escaped `!pip install` --- this is run as a separate system command. \n",
@@ -124,13 +122,13 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "05371e33",
+   "id": "01b6e940",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.942405Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.942257Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.952925Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.952485Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.679036Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.678916Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.686163Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.685904Z"
     }
    },
    "outputs": [
@@ -152,7 +150,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8071b084",
+   "id": "409d79c0",
    "metadata": {},
    "source": [
     " We see that `Salary` is missing for 59 players. The\n",
@@ -163,13 +161,13 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "aa5bc5b8",
+   "id": "3472ea4b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.955373Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.955215Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.959055Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.958533Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.687686Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.687591Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.691017Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.690736Z"
     },
     "lines_to_next_cell": 2
    },
@@ -192,7 +190,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d5017407",
+   "id": "b3a1b082",
    "metadata": {},
    "source": [
     "We first choose the best model using forward selection based on $C_p$ (6.2). This score\n",
@@ -204,13 +202,13 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "10494837",
+   "id": "4090cab5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.961940Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.961736Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.964700Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.964271Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.692519Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.692417Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.694378Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.694116Z"
     },
     "lines_to_next_cell": 0
    },
@@ -226,7 +224,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "126e9322",
+   "id": "c37b9aed",
    "metadata": {},
    "source": [
     "We need to estimate the residual variance $\\sigma^2$, which is the first argument in our scoring function above.\n",
@@ -236,13 +234,13 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "b8173cef",
+   "id": "2b85c1d6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.967518Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.967341Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.983184Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.982693Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.695743Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.695653Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.708301Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.708031Z"
     }
    },
    "outputs": [],
@@ -255,7 +253,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f873c04f",
+   "id": "e8b97efd",
    "metadata": {},
    "source": [
     "The function `sklearn_selected()` expects a scorer with just three arguments --- the last three in the definition of `nCp()` above. We use the function `partial()` first seen in Section 5.3.3 to freeze the first argument with our estimate of $\\sigma^2$."
@@ -264,13 +262,13 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "0cc8d7bd",
+   "id": "7c6f93c0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.985554Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.985389Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.987653Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.987280Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.709763Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.709684Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.711458Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.711205Z"
     },
     "lines_to_next_cell": 0
    },
@@ -281,7 +279,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3ff5a859",
+   "id": "392e5247",
    "metadata": {},
    "source": [
     "We can now use `neg_Cp()` as a scorer for model selection.\n"
@@ -289,7 +287,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2b30b7bd",
+   "id": "47461c19",
    "metadata": {},
    "source": [
     "Along with a score we need to specify the search strategy. This is done through the object\n",
@@ -302,13 +300,13 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "440b4c50",
+   "id": "4b0d8d44",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.989896Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.989765Z",
-     "iopub.status.idle": "2023-07-26T05:17:09.992061Z",
-     "shell.execute_reply": "2023-07-26T05:17:09.991502Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.712955Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.712871Z",
+     "iopub.status.idle": "2023-08-06T17:35:03.714691Z",
+     "shell.execute_reply": "2023-08-06T17:35:03.714446Z"
     }
    },
    "outputs": [],
@@ -320,7 +318,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "77079484",
+   "id": "0f8a2102",
    "metadata": {},
    "source": [
     "We now fit a linear regression model with `Salary` as outcome using forward\n",
@@ -333,13 +331,13 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "b33a8617",
+   "id": "6d3c1d1f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:09.994597Z",
-     "iopub.status.busy": "2023-07-26T05:17:09.994397Z",
-     "iopub.status.idle": "2023-07-26T05:17:10.882860Z",
-     "shell.execute_reply": "2023-07-26T05:17:10.882342Z"
+     "iopub.execute_input": "2023-08-06T17:35:03.716059Z",
+     "iopub.status.busy": "2023-08-06T17:35:03.715979Z",
+     "iopub.status.idle": "2023-08-06T17:35:04.363068Z",
+     "shell.execute_reply": "2023-08-06T17:35:04.362795Z"
     }
    },
    "outputs": [
@@ -381,7 +379,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "233e45a1",
+   "id": "cf1ad8eb",
    "metadata": {},
    "source": [
     "Using `neg_Cp` results in a smaller model, as expected, with just 10 variables selected."
@@ -390,13 +388,13 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "e7f554cf",
+   "id": "5644971d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:10.885149Z",
-     "iopub.status.busy": "2023-07-26T05:17:10.884996Z",
-     "iopub.status.idle": "2023-07-26T05:17:11.423862Z",
-     "shell.execute_reply": "2023-07-26T05:17:11.423408Z"
+     "iopub.execute_input": "2023-08-06T17:35:04.364696Z",
+     "iopub.status.busy": "2023-08-06T17:35:04.364585Z",
+     "iopub.status.idle": "2023-08-06T17:35:04.769869Z",
+     "shell.execute_reply": "2023-08-06T17:35:04.769597Z"
     }
    },
    "outputs": [
@@ -430,7 +428,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "75e8008b",
+   "id": "1db8634e",
    "metadata": {},
    "source": [
     "### Choosing Among Models Using the Validation Set Approach and Cross-Validation\n",
@@ -445,7 +443,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fc753395",
+   "id": "08bdcec5",
    "metadata": {},
    "source": [
     "Here we define a strategy that fits the full forward selection path.\n",
@@ -456,13 +454,13 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "fb7091b8",
+   "id": "23f47f58",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:11.426460Z",
-     "iopub.status.busy": "2023-07-26T05:17:11.426313Z",
-     "iopub.status.idle": "2023-07-26T05:17:11.428837Z",
-     "shell.execute_reply": "2023-07-26T05:17:11.428385Z"
+     "iopub.execute_input": "2023-08-06T17:35:04.771518Z",
+     "iopub.status.busy": "2023-08-06T17:35:04.771411Z",
+     "iopub.status.idle": "2023-08-06T17:35:04.773352Z",
+     "shell.execute_reply": "2023-08-06T17:35:04.773084Z"
     }
    },
    "outputs": [],
@@ -475,7 +473,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7f5f599f",
+   "id": "63e94493",
    "metadata": {},
    "source": [
     "We now fit the full forward-selection path on the `Hitters` data and compute the fitted values."
@@ -484,13 +482,13 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "56adc728",
+   "id": "e8e0a90d",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:11.431149Z",
-     "iopub.status.busy": "2023-07-26T05:17:11.431007Z",
-     "iopub.status.idle": "2023-07-26T05:17:11.925588Z",
-     "shell.execute_reply": "2023-07-26T05:17:11.925166Z"
+     "iopub.execute_input": "2023-08-06T17:35:04.774784Z",
+     "iopub.status.busy": "2023-08-06T17:35:04.774690Z",
+     "iopub.status.idle": "2023-08-06T17:35:05.168838Z",
+     "shell.execute_reply": "2023-08-06T17:35:05.168549Z"
     },
     "lines_to_next_cell": 2
    },
@@ -514,7 +512,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0b771d23",
+   "id": "36008ae0",
    "metadata": {},
    "source": [
     "This gives us an array of fitted values --- 20 steps in all, including the fitted mean for the null model --- which we can use to evaluate\n",
@@ -529,13 +527,13 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "387267d9",
+   "id": "4e44d7ad",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:11.928605Z",
-     "iopub.status.busy": "2023-07-26T05:17:11.928329Z",
-     "iopub.status.idle": "2023-07-26T05:17:12.168674Z",
-     "shell.execute_reply": "2023-07-26T05:17:12.165742Z"
+     "iopub.execute_input": "2023-08-06T17:35:05.170387Z",
+     "iopub.status.busy": "2023-08-06T17:35:05.170300Z",
+     "iopub.status.idle": "2023-08-06T17:35:05.352387Z",
+     "shell.execute_reply": "2023-08-06T17:35:05.350850Z"
     },
     "lines_to_next_cell": 0
    },
@@ -570,7 +568,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fc09acdc",
+   "id": "f0113aa5",
    "metadata": {},
    "source": [
     "Notice the expression `None` in `Y[:,None]` above.\n",
@@ -580,7 +578,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2a1511cd",
+   "id": "e3daf6ac",
    "metadata": {},
    "source": [
     "We are now ready to use cross-validation to estimate test error along\n",
@@ -598,14 +596,15 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "0047ba88",
+   "id": "c8b63bdf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:12.180601Z",
-     "iopub.status.busy": "2023-07-26T05:17:12.179903Z",
-     "iopub.status.idle": "2023-07-26T05:17:14.657028Z",
-     "shell.execute_reply": "2023-07-26T05:17:14.656647Z"
-    }
+     "iopub.execute_input": "2023-08-06T17:35:05.356634Z",
+     "iopub.status.busy": "2023-08-06T17:35:05.356263Z",
+     "iopub.status.idle": "2023-08-06T17:35:07.379649Z",
+     "shell.execute_reply": "2023-08-06T17:35:07.379349Z"
+    },
+    "lines_to_next_cell": 0
    },
    "outputs": [
     {
@@ -633,9 +632,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c6df5d31",
+   "id": "734ebc1a",
    "metadata": {},
    "source": [
+    "`skm.cross_val_predict()`\n",
     "The prediction matrix `Yhat_cv` is the same shape as `Yhat_in`; the difference is that the predictions in each row, corresponding to a particular sample index, were made from models fit on a training fold that did not include that row.\n",
     "\n",
     "At each model along the path, we compute the MSE in each of the cross-validation folds.\n",
@@ -650,13 +650,13 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "27b0eb63",
+   "id": "c2a5b743",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:14.659368Z",
-     "iopub.status.busy": "2023-07-26T05:17:14.659240Z",
-     "iopub.status.idle": "2023-07-26T05:17:14.663478Z",
-     "shell.execute_reply": "2023-07-26T05:17:14.663025Z"
+     "iopub.execute_input": "2023-08-06T17:35:07.381451Z",
+     "iopub.status.busy": "2023-08-06T17:35:07.381333Z",
+     "iopub.status.idle": "2023-08-06T17:35:07.384547Z",
+     "shell.execute_reply": "2023-08-06T17:35:07.384245Z"
     }
    },
    "outputs": [
@@ -682,7 +682,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "223556f8",
+   "id": "eeace224",
    "metadata": {},
    "source": [
     "We now add the cross-validation error estimates to our MSE plot.\n",
@@ -692,13 +692,13 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "a45fe587",
+   "id": "678b6284",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:14.665854Z",
-     "iopub.status.busy": "2023-07-26T05:17:14.665694Z",
-     "iopub.status.idle": "2023-07-26T05:17:14.764103Z",
-     "shell.execute_reply": "2023-07-26T05:17:14.763688Z"
+     "iopub.execute_input": "2023-08-06T17:35:07.385961Z",
+     "iopub.status.busy": "2023-08-06T17:35:07.385880Z",
+     "iopub.status.idle": "2023-08-06T17:35:07.473192Z",
+     "shell.execute_reply": "2023-08-06T17:35:07.472899Z"
     }
    },
    "outputs": [
@@ -727,24 +727,24 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fb4fa850",
+   "id": "5e27d9a1",
    "metadata": {},
    "source": [
     "To repeat the above using the validation set approach, we simply change our\n",
     "`cv` argument to a validation set: one random split of the data into a test and training. We choose a test size\n",
-    "of 20%, similar to the size of each test set in 5-fold cross-validation."
+    "of 20%, similar to the size of each test set in 5-fold cross-validation.`skm.ShuffleSplit()`"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "c71c2079",
+   "id": "f55f5449",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:14.766668Z",
-     "iopub.status.busy": "2023-07-26T05:17:14.766176Z",
-     "iopub.status.idle": "2023-07-26T05:17:15.254311Z",
-     "shell.execute_reply": "2023-07-26T05:17:15.253748Z"
+     "iopub.execute_input": "2023-08-06T17:35:07.474839Z",
+     "iopub.status.busy": "2023-08-06T17:35:07.474729Z",
+     "iopub.status.idle": "2023-08-06T17:35:07.866358Z",
+     "shell.execute_reply": "2023-08-06T17:35:07.866074Z"
     },
     "lines_to_next_cell": 0
    },
@@ -763,7 +763,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d34bb7ab",
+   "id": "b778cde1",
    "metadata": {},
    "source": [
     " As for the in-sample MSE case, the validation set approach does not provide standard errors."
@@ -772,13 +772,13 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "2ff34edf",
+   "id": "791c91cf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:15.257176Z",
-     "iopub.status.busy": "2023-07-26T05:17:15.256855Z",
-     "iopub.status.idle": "2023-07-26T05:17:15.361521Z",
-     "shell.execute_reply": "2023-07-26T05:17:15.360872Z"
+     "iopub.execute_input": "2023-08-06T17:35:07.868260Z",
+     "iopub.status.busy": "2023-08-06T17:35:07.868151Z",
+     "iopub.status.idle": "2023-08-06T17:35:07.959616Z",
+     "shell.execute_reply": "2023-08-06T17:35:07.959298Z"
     },
     "lines_to_next_cell": 2
    },
@@ -808,7 +808,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e5517334",
+   "id": "13144579",
    "metadata": {},
    "source": [
     "### Best Subset Selection\n",
@@ -825,13 +825,13 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "845f3fa0",
+   "id": "2c796192",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:15.364952Z",
-     "iopub.status.busy": "2023-07-26T05:17:15.364689Z",
-     "iopub.status.idle": "2023-07-26T05:17:15.379444Z",
-     "shell.execute_reply": "2023-07-26T05:17:15.379028Z"
+     "iopub.execute_input": "2023-08-06T17:35:07.961298Z",
+     "iopub.status.busy": "2023-08-06T17:35:07.961209Z",
+     "iopub.status.idle": "2023-08-06T17:35:07.972689Z",
+     "shell.execute_reply": "2023-08-06T17:35:07.972416Z"
     },
     "lines_to_next_cell": 0
    },
@@ -844,7 +844,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4c0d0e19",
+   "id": "95a3f639",
    "metadata": {},
    "source": [
     "Here we excluded the first column corresponding to the intercept, as\n",
@@ -854,13 +854,13 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "e9f943e7",
+   "id": "abb9e7ac",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:15.381427Z",
-     "iopub.status.busy": "2023-07-26T05:17:15.381284Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.000267Z",
-     "shell.execute_reply": "2023-07-26T05:17:17.999357Z"
+     "iopub.execute_input": "2023-08-06T17:35:07.974253Z",
+     "iopub.status.busy": "2023-08-06T17:35:07.974167Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.125189Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.124893Z"
     }
    },
    "outputs": [
@@ -900,7 +900,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "67ef90b5",
+   "id": "6c577e2a",
    "metadata": {},
    "source": [
     "The function `fit_path()` returns a list whose values include the fitted coefficients as `B`, an intercept as `B0`, as well as a few other attributes related to the particular path algorithm used. Such details are beyond the scope of this book."
@@ -909,13 +909,13 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "657ac171",
+   "id": "70f1c6c2",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.003862Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.003705Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.006563Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.006222Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.126871Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.126769Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.129192Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.128949Z"
     },
     "lines_to_next_cell": 0
    },
@@ -944,7 +944,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2c9e040a",
+   "id": "1882702b",
    "metadata": {},
    "source": [
     "In the example above, we see that at the fourth step in the path, we have two nonzero coefficients in `'B'`, corresponding to the value $0.114$ for the penalty parameter `lambda_0`.\n",
@@ -974,13 +974,13 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "e576ad54",
+   "id": "9f1fc533",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.008980Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.008783Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.078116Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.077656Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.130683Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.130585Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.201951Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.201689Z"
     },
     "lines_to_next_cell": 0
    },
@@ -989,405 +989,405 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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"
      ]
     },
@@ -1416,7 +1416,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5ba706cd",
+   "id": "cefe307b",
    "metadata": {},
    "source": [
     "Here we extract the array of coefficients corresponding to the solutions along the regularization path.\n",
@@ -1441,13 +1441,13 @@
   {
    "cell_type": "code",
    "execution_count": 23,
-   "id": "3ef15192",
+   "id": "642287d1",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.080752Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.080552Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.094265Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.093783Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.203715Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.203613Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.214312Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.214061Z"
     }
    },
    "outputs": [
@@ -1852,7 +1852,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f73f5191",
+   "id": "8e2a5cd7",
    "metadata": {},
    "source": [
     "We plot the paths to get a sense of how the coefficients vary with $\\lambda$.\n",
@@ -1863,13 +1863,13 @@
   {
    "cell_type": "code",
    "execution_count": 24,
-   "id": "40b67c85",
+   "id": "734c1a05",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.097009Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.096807Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.336481Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.335993Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.215773Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.215682Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.473871Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.473500Z"
     },
     "lines_to_next_cell": 0
    },
@@ -1895,7 +1895,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "84e52006",
+   "id": "75cfe676",
    "metadata": {},
    "source": [
     "(We have used `latex` formatting in the horizontal label, in order to format the Greek $\\lambda$ appropriately.) \n",
@@ -1908,13 +1908,13 @@
   {
    "cell_type": "code",
    "execution_count": 25,
-   "id": "d14bd86c",
+   "id": "5a55b76b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.338709Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.338591Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.342588Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.342104Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.475713Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.475586Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.479270Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.479006Z"
     }
    },
    "outputs": [
@@ -1956,7 +1956,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98ba8e99",
+   "id": "a8f4071c",
    "metadata": {},
    "source": [
     "Let’s compute the $\\ell_2$ norm of the standardized coefficients."
@@ -1965,13 +1965,13 @@
   {
    "cell_type": "code",
    "execution_count": 26,
-   "id": "759e215a",
+   "id": "cdbee899",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.344904Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.344761Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.347862Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.347417Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.480798Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.480689Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.483091Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.482738Z"
     }
    },
    "outputs": [
@@ -1992,7 +1992,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ce79e7cb",
+   "id": "2511270d",
    "metadata": {},
    "source": [
     "In contrast, here is the $\\ell_2$ norm when $\\lambda$ is 2.44e-01.\n",
@@ -2003,13 +2003,13 @@
   {
    "cell_type": "code",
    "execution_count": 27,
-   "id": "b58d5ccb",
+   "id": "23fe1cb5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.350171Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.350022Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.353142Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.352734Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.484686Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.484597Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.487152Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.486881Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2032,7 +2032,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc9a1f70",
+   "id": "c610fcf7",
    "metadata": {},
    "source": [
     "Above we normalized `X` upfront, and fit the ridge model using `Xs`.\n",
@@ -2044,13 +2044,13 @@
   {
    "cell_type": "code",
    "execution_count": 28,
-   "id": "74b5cae2",
+   "id": "fa46c4d0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.355548Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.355367Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.370341Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.369949Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.488575Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.488492Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.500853Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.500570Z"
     }
    },
    "outputs": [
@@ -2058,14 +2058,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
     {
      "data": {
       "text/html": [
-       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
+       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
        "                ('ridge', ElasticNet(alpha=0.24374766133488554, l1_ratio=0))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
       ],
@@ -2088,7 +2088,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7a69991b",
+   "id": "a5607efa",
    "metadata": {},
    "source": [
     "We show that it gives the same $\\ell_2$ norm as in our previous fit on the standardized data."
@@ -2097,13 +2097,13 @@
   {
    "cell_type": "code",
    "execution_count": 29,
-   "id": "a89989c3",
+   "id": "8e775d4c",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.372736Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.372583Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.375751Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.375223Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.502445Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.502342Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.504676Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.504390Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2125,7 +2125,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c86254e4",
+   "id": "06771f4e",
    "metadata": {},
    "source": [
     " Notice that the operation `pipe.fit(X, Y)` above has changed the `ridge` object, and in particular has added attributes such as `coef_` that were not there before. \n",
@@ -2144,13 +2144,13 @@
   {
    "cell_type": "code",
    "execution_count": 30,
-   "id": "3eb41945",
+   "id": "531f7c0e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.377750Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.377627Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.385518Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.385025Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.506171Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.506087Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.513511Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.513210Z"
     }
    },
    "outputs": [
@@ -2158,7 +2158,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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"
      ]
     },
@@ -2188,7 +2188,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "660f7c63",
+   "id": "951f3189",
    "metadata": {},
    "source": [
     "The test MSE is 1.342e+05.  Note\n",
@@ -2202,13 +2202,13 @@
   {
    "cell_type": "code",
    "execution_count": 31,
-   "id": "635bc363",
+   "id": "9d6abcd6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.387843Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.387682Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.396692Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.396288Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.515133Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.515021Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.522324Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.522079Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2217,7 +2217,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
@@ -2244,7 +2244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c14ad9a1",
+   "id": "60702c2d",
    "metadata": {},
    "source": [
     "Obviously choosing $\\lambda=0.01$ is arbitrary,  so we will  use cross-validation or the validation-set\n",
@@ -2259,13 +2259,13 @@
   {
    "cell_type": "code",
    "execution_count": 32,
-   "id": "e117267f",
+   "id": "4009c7c9",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.399267Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.399145Z",
-     "iopub.status.idle": "2023-07-26T05:17:18.894315Z",
-     "shell.execute_reply": "2023-07-26T05:17:18.893964Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.523797Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.523701Z",
+     "iopub.status.idle": "2023-08-06T17:35:10.984369Z",
+     "shell.execute_reply": "2023-08-06T17:35:10.984118Z"
     }
    },
    "outputs": [
@@ -2273,214 +2273,214 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
     {
      "data": {
       "text/html": [
-       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
+       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
        "                ('ridge', ElasticNet(alpha=0.005899006046740856, l1_ratio=0))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
       ],
@@ -2507,7 +2507,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bc09d074",
+   "id": "8e22f625",
    "metadata": {},
    "source": [
     "Alternatively, we can use 5-fold cross-validation."
@@ -2516,13 +2516,13 @@
   {
    "cell_type": "code",
    "execution_count": 33,
-   "id": "0037e9e4",
+   "id": "1fd51cd6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:18.896714Z",
-     "iopub.status.busy": "2023-07-26T05:17:18.896538Z",
-     "iopub.status.idle": "2023-07-26T05:17:22.201859Z",
-     "shell.execute_reply": "2023-07-26T05:17:22.201489Z"
+     "iopub.execute_input": "2023-08-06T17:35:10.985928Z",
+     "iopub.status.busy": "2023-08-06T17:35:10.985818Z",
+     "iopub.status.idle": "2023-08-06T17:35:14.088216Z",
+     "shell.execute_reply": "2023-08-06T17:35:14.087921Z"
     },
     "lines_to_next_cell": 0
    },
@@ -2531,1014 +2531,1014 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
     {
      "data": {
       "text/html": [
-       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
+       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
        "                ('ridge', ElasticNet(alpha=0.01185247763144249, l1_ratio=0))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
       ],
@@ -3564,7 +3564,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9690407d",
+   "id": "245526c5",
    "metadata": {},
    "source": [
     "Recall we set up the `kfold` object for 5-fold cross-validation on page 296. We now plot the cross-validated MSE as a function of $-\\log(\\lambda)$, which has shrinkage decreasing from left\n",
@@ -3574,13 +3574,13 @@
   {
    "cell_type": "code",
    "execution_count": 34,
-   "id": "71f0f5c5",
+   "id": "1679fd6a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:22.203851Z",
-     "iopub.status.busy": "2023-07-26T05:17:22.203701Z",
-     "iopub.status.idle": "2023-07-26T05:17:22.319890Z",
-     "shell.execute_reply": "2023-07-26T05:17:22.318803Z"
+     "iopub.execute_input": "2023-08-06T17:35:14.089895Z",
+     "iopub.status.busy": "2023-08-06T17:35:14.089782Z",
+     "iopub.status.idle": "2023-08-06T17:35:14.187870Z",
+     "shell.execute_reply": "2023-08-06T17:35:14.187444Z"
     }
    },
    "outputs": [
@@ -3607,7 +3607,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "11087e26",
+   "id": "36cc5ca2",
    "metadata": {},
    "source": [
     "One can cross-validate different metrics to choose a parameter. The default\n",
@@ -3618,13 +3618,13 @@
   {
    "cell_type": "code",
    "execution_count": 35,
-   "id": "fb265379",
+   "id": "f59557ed",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:22.322704Z",
-     "iopub.status.busy": "2023-07-26T05:17:22.322434Z",
-     "iopub.status.idle": "2023-07-26T05:17:25.602424Z",
-     "shell.execute_reply": "2023-07-26T05:17:25.601831Z"
+     "iopub.execute_input": "2023-08-06T17:35:14.189531Z",
+     "iopub.status.busy": "2023-08-06T17:35:14.189417Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.306928Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.306627Z"
     }
    },
    "outputs": [
@@ -3632,1014 +3632,1014 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective 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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
     {
      "data": {
       "text/html": [
-       "
GridSearchCV(cv=KFold(n_splits=5, random_state=0, shuffle=True),\n",
+       "
GridSearchCV(cv=KFold(n_splits=5, random_state=0, shuffle=True),\n",
        "             estimator=Pipeline(steps=[('scaler', StandardScaler()),\n",
        "                                       ('ridge',\n",
        "                                        ElasticNet(alpha=10000000000.0,\n",
@@ -4699,7 +4699,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9881fe49",
+   "id": "5ac19760",
    "metadata": {},
    "source": [
     "Finally, let’s plot the results for cross-validated $R^2$."
@@ -4708,13 +4708,13 @@
   {
    "cell_type": "code",
    "execution_count": 36,
-   "id": "79616f48",
+   "id": "12d94ae6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:25.604857Z",
-     "iopub.status.busy": "2023-07-26T05:17:25.604672Z",
-     "iopub.status.idle": "2023-07-26T05:17:25.718682Z",
-     "shell.execute_reply": "2023-07-26T05:17:25.718164Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.308495Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.308379Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.402970Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.402653Z"
     },
     "lines_to_next_cell": 2
    },
@@ -4741,7 +4741,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5e700bf5",
+   "id": "f9eda9aa",
    "metadata": {},
    "source": [
     "### Fast Cross-Validation for Solution Paths\n",
@@ -4757,13 +4757,13 @@
   {
    "cell_type": "code",
    "execution_count": 37,
-   "id": "11e55883",
+   "id": "b1fd1281",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:25.721504Z",
-     "iopub.status.busy": "2023-07-26T05:17:25.721335Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.086495Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.085843Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.404648Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.404531Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.759816Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.759499Z"
     }
    },
    "outputs": [
@@ -4771,2014 +4771,2014 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
     {
      "data": {
       "text/html": [
-       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
+       "
Pipeline(steps=[('scaler', StandardScaler()),\n",
        "                ('ridge',\n",
        "                 ElasticNetCV(alphas=array([2.22093791e+05, 1.76005531e+05, 1.39481373e+05, 1.10536603e+05,\n",
        "       8.75983676e+04, 6.94202082e+04, 5.50143278e+04, 4.35979140e+04,\n",
@@ -6850,7 +6850,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "75eb9d33",
+   "id": "da8395bb",
    "metadata": {},
    "source": [
     "Let’s produce a plot again of the cross-validation error to see that\n",
@@ -6860,13 +6860,13 @@
   {
    "cell_type": "code",
    "execution_count": 38,
-   "id": "d107f961",
+   "id": "5cf09512",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.090198Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.090011Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.211437Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.210939Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.761454Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.761346Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.865044Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.864747Z"
     }
    },
    "outputs": [
@@ -6895,7 +6895,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "23a89187",
+   "id": "6f5eb495",
    "metadata": {},
    "source": [
     "We see that the value of $\\lambda$ that results in the\n",
@@ -6907,13 +6907,13 @@
   {
    "cell_type": "code",
    "execution_count": 39,
-   "id": "21d65d1f",
+   "id": "a8d6770f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.214203Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.213975Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.217529Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.216950Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.866746Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.866628Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.869096Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.868823Z"
     }
    },
    "outputs": [
@@ -6934,7 +6934,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e8bb2108",
+   "id": "4da37400",
    "metadata": {},
    "source": [
     "This represents a further improvement over the test MSE that we got\n",
@@ -6946,13 +6946,13 @@
   {
    "cell_type": "code",
    "execution_count": 40,
-   "id": "11373de9",
+   "id": "852b1e39",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.219927Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.219801Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.222854Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.222347Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.870890Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.870776Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.873149Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.872893Z"
     },
     "lines_to_next_cell": 0
    },
@@ -6978,7 +6978,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8e7ab31e",
+   "id": "93ea5623",
    "metadata": {},
    "source": [
     "As expected, none of the coefficients are zero—ridge regression does\n",
@@ -6987,7 +6987,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6e2cb7c4",
+   "id": "3e01383a",
    "metadata": {},
    "source": [
     "### Evaluating Test Error of Cross-Validated Ridge\n",
@@ -7011,13 +7011,13 @@
   {
    "cell_type": "code",
    "execution_count": 41,
-   "id": "72181964",
+   "id": "81f6259f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.225411Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.225192Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.228812Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.228380Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.874806Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.874678Z",
+     "iopub.status.idle": "2023-08-06T17:35:17.876932Z",
+     "shell.execute_reply": "2023-08-06T17:35:17.876690Z"
     }
    },
    "outputs": [],
@@ -7038,13 +7038,13 @@
   {
    "cell_type": "code",
    "execution_count": 42,
-   "id": "4c3054b5",
+   "id": "e44495e5",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.231904Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.231669Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.556426Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.556096Z"
+     "iopub.execute_input": "2023-08-06T17:35:17.878420Z",
+     "iopub.status.busy": "2023-08-06T17:35:17.878316Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.202556Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.202283Z"
     },
     "lines_to_next_cell": 0
    },
@@ -7053,2007 +7053,2007 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
+      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:614: UserWarning: Coordinate descent without L1 regularization may lead to unexpected results and is discouraged. Set l1_ratio > 0 to add L1 regularization.\n",
       "  model = cd_fast.enet_coordinate_descent_gram(\n",
-      "/Users/jonathantaylor/anaconda3/envs/islp_freeze_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:617: 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/islp_freeze_311/lib/python3.11/site-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_39/lib/python3.9/site-packages/sklearn/linear_model/_coordinate_descent.py:631: ConvergenceWarning: Objective did 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/islp_freeze_311/lib/python3.11/site-packages/sklearn/linear_model/_coordinate_descent.py:628: ConvergenceWarning: Objective did 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"
      ]
     },
@@ -9079,7 +9079,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cf2eba05",
+   "id": "9fed598e",
    "metadata": {},
    "source": [
     "    "
@@ -9087,7 +9087,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f2f899f2",
+   "id": "9ecaca1a",
    "metadata": {},
    "source": [
     "### The Lasso\n",
@@ -9104,13 +9104,13 @@
   {
    "cell_type": "code",
    "execution_count": 43,
-   "id": "72bb0c1d",
+   "id": "aae18029",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.560895Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.560717Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.616139Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.615605Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.204830Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.204720Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.262253Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.261987Z"
     },
     "lines_to_next_cell": 2
    },
@@ -9140,13 +9140,13 @@
   {
    "cell_type": "code",
    "execution_count": 44,
-   "id": "69adc7ac",
+   "id": "b6d9dd06",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.618605Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.618409Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.629654Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.629177Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.263674Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.263592Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.274556Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.274311Z"
     },
     "lines_to_next_cell": 0
    },
@@ -9163,7 +9163,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "cc6d84d3",
+   "id": "52817006",
    "metadata": {},
    "source": [
     "We can see from the coefficient plot of the standardized coefficients that depending on the choice of\n",
@@ -9174,13 +9174,13 @@
   {
    "cell_type": "code",
    "execution_count": 45,
-   "id": "2aa75789",
+   "id": "6e5f9a74",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.632157Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.631965Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.833444Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.832719Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.276056Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.275973Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.444193Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.443901Z"
     },
     "lines_to_next_cell": 0
    },
@@ -9206,7 +9206,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "87d43d52",
+   "id": "2e1e6626",
    "metadata": {},
    "source": [
     "The smallest cross-validated error is lower than the test set MSE of the null model\n",
@@ -9217,20 +9217,20 @@
   {
    "cell_type": "code",
    "execution_count": 46,
-   "id": "e38c9bed",
+   "id": "9b57296a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.836589Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.836233Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.841023Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.840686Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.445914Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.445792Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.448316Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.448072Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "114690.73118253548"
+       "114690.73118253727"
       ]
      },
      "execution_count": 46,
@@ -9244,7 +9244,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d091d74c",
+   "id": "5f35282c",
    "metadata": {},
    "source": [
     "Let’s again produce a plot of the cross-validation error.\n"
@@ -9253,13 +9253,13 @@
   {
    "cell_type": "code",
    "execution_count": 47,
-   "id": "53c42724",
+   "id": "b1b1a84a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.843812Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.843647Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.968792Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.968349Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.449905Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.449752Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.555457Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.555156Z"
     }
    },
    "outputs": [
@@ -9287,7 +9287,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fad5c750",
+   "id": "7250e5c0",
    "metadata": {},
    "source": [
     "However, the lasso has a substantial advantage over ridge regression\n",
@@ -9300,13 +9300,13 @@
   {
    "cell_type": "code",
    "execution_count": 48,
-   "id": "5f4942ba",
+   "id": "44246aee",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.971271Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.971065Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.974897Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.973908Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.557237Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.557121Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.559615Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.559331Z"
     }
    },
    "outputs": [
@@ -9331,7 +9331,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "af600bbc",
+   "id": "bc08d038",
    "metadata": {},
    "source": [
     "As in ridge regression, we could evaluate the test error\n",
@@ -9343,7 +9343,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8d9aeb7b",
+   "id": "a55364da",
    "metadata": {},
    "source": [
     "## PCR and PLS Regression\n",
@@ -9353,7 +9353,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "1ef4790c",
+   "id": "2806f021",
    "metadata": {},
    "source": [
     "Principal components regression (PCR) can be performed using\n",
@@ -9370,13 +9370,13 @@
   {
    "cell_type": "code",
    "execution_count": 49,
-   "id": "72a876bb",
+   "id": "33a88f6a",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.977635Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.977456Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.983252Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.982747Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.561277Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.561175Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.565614Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.565342Z"
     }
    },
    "outputs": [
@@ -9402,7 +9402,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "77d5a225",
+   "id": "4f94c0cc",
    "metadata": {},
    "source": [
     "When performing PCA, the results vary depending\n",
@@ -9414,13 +9414,13 @@
   {
    "cell_type": "code",
    "execution_count": 50,
-   "id": "e0e821c6",
+   "id": "86fa37a7",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.985960Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.985773Z",
-     "iopub.status.idle": "2023-07-26T05:17:26.991831Z",
-     "shell.execute_reply": "2023-07-26T05:17:26.991247Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.567133Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.567034Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.570714Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.570443Z"
     }
    },
    "outputs": [
@@ -9445,7 +9445,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c5ebec9",
+   "id": "05e0acfe",
    "metadata": {},
    "source": [
     "We can of course use CV to choose the number of components, by\n",
@@ -9457,20 +9457,20 @@
   {
    "cell_type": "code",
    "execution_count": 51,
-   "id": "1ac6886c",
+   "id": "1e84065b",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:26.994661Z",
-     "iopub.status.busy": "2023-07-26T05:17:26.994482Z",
-     "iopub.status.idle": "2023-07-26T05:17:27.138949Z",
-     "shell.execute_reply": "2023-07-26T05:17:27.138448Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.572236Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.572149Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.692323Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.692024Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "
GridSearchCV(cv=KFold(n_splits=5, random_state=0, shuffle=True),\n",
+       "
GridSearchCV(cv=KFold(n_splits=5, random_state=0, shuffle=True),\n",
        "             estimator=Pipeline(steps=[('scaler', StandardScaler()),\n",
        "                                       ('pca', PCA(n_components=2)),\n",
        "                                       ('linreg', LinearRegression())]),\n",
@@ -9508,7 +9508,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dc21d28d",
+   "id": "965677ed",
    "metadata": {},
    "source": [
     "Let’s plot the results as we have for other methods."
@@ -9517,13 +9517,13 @@
   {
    "cell_type": "code",
    "execution_count": 52,
-   "id": "5e0c5a96",
+   "id": "ff432faf",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:27.141752Z",
-     "iopub.status.busy": "2023-07-26T05:17:27.141555Z",
-     "iopub.status.idle": "2023-07-26T05:17:27.257460Z",
-     "shell.execute_reply": "2023-07-26T05:17:27.256920Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.693955Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.693854Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.790857Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.790544Z"
     }
    },
    "outputs": [
@@ -9552,7 +9552,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0c0aadc3",
+   "id": "8d3ca451",
    "metadata": {},
    "source": [
     "We see that the smallest cross-validation error occurs when\n",
@@ -9572,13 +9572,13 @@
   {
    "cell_type": "code",
    "execution_count": 53,
-   "id": "9df0fb7f",
+   "id": "57d21a61",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:27.260143Z",
-     "iopub.status.busy": "2023-07-26T05:17:27.259963Z",
-     "iopub.status.idle": "2023-07-26T05:17:27.267101Z",
-     "shell.execute_reply": "2023-07-26T05:17:27.266627Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.792385Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.792283Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.797861Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.797615Z"
     },
     "lines_to_next_cell": 2
    },
@@ -9606,7 +9606,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "89f0e0bb",
+   "id": "333d11bd",
    "metadata": {},
    "source": [
     "The `explained_variance_ratio_`\n",
@@ -9618,13 +9618,13 @@
   {
    "cell_type": "code",
    "execution_count": 54,
-   "id": "458c21a4",
+   "id": "8d170a51",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:27.269230Z",
-     "iopub.status.busy": "2023-07-26T05:17:27.269087Z",
-     "iopub.status.idle": "2023-07-26T05:17:27.272035Z",
-     "shell.execute_reply": "2023-07-26T05:17:27.271586Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.799375Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.799269Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.801474Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.801155Z"
     }
    },
    "outputs": [
@@ -9645,7 +9645,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bdd994d2",
+   "id": "e0413213",
    "metadata": {},
    "source": [
     "Briefly, we can think of\n",
@@ -9660,7 +9660,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "af5147dc",
+   "id": "e04f26d1",
    "metadata": {},
    "source": [
     "### Partial Least Squares\n",
@@ -9673,20 +9673,20 @@
   {
    "cell_type": "code",
    "execution_count": 55,
-   "id": "f49d464e",
+   "id": "9d35e0d6",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:27.274642Z",
-     "iopub.status.busy": "2023-07-26T05:17:27.274472Z",
-     "iopub.status.idle": "2023-07-26T05:17:27.279195Z",
-     "shell.execute_reply": "2023-07-26T05:17:27.278730Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.802981Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.802864Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.806324Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.806053Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "
PLSRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
+       "
PLSRegression()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
"
       ],
       "text/plain": [
        "PLSRegression()"
@@ -9705,7 +9705,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7a07b988",
+   "id": "5945c8cf",
    "metadata": {},
    "source": [
     "As was the case in PCR, we will want to\n",
@@ -9715,20 +9715,20 @@
   {
    "cell_type": "code",
    "execution_count": 56,
-   "id": "8e118b5b",
+   "id": "35867372",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2023-07-26T05:17:27.281479Z",
-     "iopub.status.busy": "2023-07-26T05:17:27.281289Z",
-     "iopub.status.idle": "2023-07-26T05:17:27.395617Z",
-     "shell.execute_reply": "2023-07-26T05:17:27.395127Z"
+     "iopub.execute_input": "2023-08-06T17:35:18.807917Z",
+     "iopub.status.busy": "2023-08-06T17:35:18.807830Z",
+     "iopub.status.idle": "2023-08-06T17:35:18.913647Z",
+     "shell.execute_reply": "2023-08-06T17:35:18.913377Z"
     }
    },
    "outputs": [
     {
      "data": {
       "text/html": [
-       "
GridSearchCV(cv=KFold(n_splits=5, random_state=0, shuffle=True),\n",
+       "
GridSearchCV(cv=KFold(n_splits=5, random_state=0, shuffle=True),\n",
        "             estimator=PLSRegression(),\n",
        "             param_grid={'n_components': range(1, 20)},\n",
        "             scoring='neg_mean_squared_error')
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.