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updating lab version

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Jonathan Taylor committed 2026-02-02 17:04:01 -08:00
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Ch02-statlearn-lab.ipynb
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Ch03-linreg-lab.Rmd
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@@ -13,11 +13,11 @@ jupyter:
# Linear Regression
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch03-linreg-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch03-linreg-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch03-linreg-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch03-linreg-lab.ipynb)
Ch03-linreg-lab.ipynb
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@@ -7,11 +7,11 @@
"source": [
"# Linear Regression\n",
"\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch03-linreg-lab.ipynb\">\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch03-linreg-lab.ipynb\">\n",
"<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch03-linreg-lab.ipynb)\n"
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch03-linreg-lab.ipynb)\n"
]
},
{
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@@ -1003,10 +1003,10 @@
" <th>Method:</th> <td>Least Squares</td> <th> F-statistic: </th> <td> 601.6</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Date:</th> <td>Thu, 03 Apr 2025</td> <th> Prob (F-statistic):</th> <td>5.08e-88</td>\n",
" <th>Date:</th> <td>Mon, 02 Feb 2026</td> <th> Prob (F-statistic):</th> <td>5.08e-88</td>\n",
"</tr>\n",
"<tr>\n",
" <th>Time:</th> <td>15:32:50</td> <th> Log-Likelihood: </th> <td> -1641.5</td>\n",
" <th>Time:</th> <td>15:39:30</td> <th> Log-Likelihood: </th> <td> -1641.5</td>\n",
"</tr>\n",
"<tr>\n",
" <th>No. Observations:</th> <td> 506</td> <th> AIC: </th> <td> 3287.</td>\n",
@@ -1054,8 +1054,8 @@
"\\textbf{Dep. Variable:} & medv & \\textbf{ R-squared: } & 0.544 \\\\\n",
"\\textbf{Model:} & OLS & \\textbf{ Adj. R-squared: } & 0.543 \\\\\n",
"\\textbf{Method:} & Least Squares & \\textbf{ F-statistic: } & 601.6 \\\\\n",
"\\textbf{Date:} & Thu, 03 Apr 2025 & \\textbf{ Prob (F-statistic):} & 5.08e-88 \\\\\n",
"\\textbf{Time:} & 15:32:50 & \\textbf{ Log-Likelihood: } & -1641.5 \\\\\n",
"\\textbf{Date:} & Mon, 02 Feb 2026 & \\textbf{ Prob (F-statistic):} & 5.08e-88 \\\\\n",
"\\textbf{Time:} & 15:39:30 & \\textbf{ Log-Likelihood: } & -1641.5 \\\\\n",
"\\textbf{No. Observations:} & 506 & \\textbf{ AIC: } & 3287. \\\\\n",
"\\textbf{Df Residuals:} & 504 & \\textbf{ BIC: } & 3295. \\\\\n",
"\\textbf{Df Model:} & 1 & \\textbf{ } & \\\\\n",
@@ -1090,8 +1090,8 @@
"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: Thu, 03 Apr 2025 Prob (F-statistic): 5.08e-88\n",
"Time: 15:32:50 Log-Likelihood: -1641.5\n",
"Date: Mon, 02 Feb 2026 Prob (F-statistic): 5.08e-88\n",
"Time: 15:39:30 Log-Likelihood: -1641.5\n",
"No. Observations: 506 AIC: 3287.\n",
"Df Residuals: 504 BIC: 3295.\n",
"Df Model: 1 \n",
@@ -1137,10 +1137,10 @@
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"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70382/1591428221.py:3: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
" results.params[0],\n",
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70382/1591428221.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
" results.params[1],\n"
]
},
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
@@ -1549,17 +1539,17 @@
"id": "74be2100",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:50.888362Z",
"iopub.status.busy": "2025-04-03T19:32:50.887998Z",
"iopub.status.idle": "2025-04-03T19:32:50.983668Z",
"shell.execute_reply": "2025-04-03T19:32:50.983019Z"
"iopub.execute_input": "2026-02-02T23:39:30.830030Z",
"iopub.status.busy": "2026-02-02T23:39:30.829002Z",
"iopub.status.idle": "2026-02-02T23:39:30.947889Z",
"shell.execute_reply": "2026-02-02T23:39:30.947633Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1597,10 +1587,10 @@
"id": "db8bc925",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:50.987634Z",
"iopub.status.busy": "2025-04-03T19:32:50.987335Z",
"iopub.status.idle": "2025-04-03T19:32:51.093124Z",
"shell.execute_reply": "2025-04-03T19:32:51.092860Z"
"iopub.execute_input": "2026-02-02T23:39:30.949366Z",
"iopub.status.busy": "2026-02-02T23:39:30.949271Z",
"iopub.status.idle": "2026-02-02T23:39:31.019326Z",
"shell.execute_reply": "2026-02-02T23:39:31.019079Z"
},
"lines_to_next_cell": 0
},
@@ -1617,7 +1607,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1665,10 +1655,10 @@
"id": "e479373c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.094541Z",
"iopub.status.busy": "2025-04-03T19:32:51.094455Z",
"iopub.status.idle": "2025-04-03T19:32:51.105229Z",
"shell.execute_reply": "2025-04-03T19:32:51.104994Z"
"iopub.execute_input": "2026-02-02T23:39:31.020681Z",
"iopub.status.busy": "2026-02-02T23:39:31.020598Z",
"iopub.status.idle": "2026-02-02T23:39:31.030887Z",
"shell.execute_reply": "2026-02-02T23:39:31.030658Z"
},
"lines_to_next_cell": 0
},
@@ -1763,10 +1753,10 @@
"id": "b903170c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.106458Z",
"iopub.status.busy": "2025-04-03T19:32:51.106379Z",
"iopub.status.idle": "2025-04-03T19:32:51.108676Z",
"shell.execute_reply": "2025-04-03T19:32:51.108453Z"
"iopub.execute_input": "2026-02-02T23:39:31.032055Z",
"iopub.status.busy": "2026-02-02T23:39:31.031989Z",
"iopub.status.idle": "2026-02-02T23:39:31.034213Z",
"shell.execute_reply": "2026-02-02T23:39:31.033996Z"
}
},
"outputs": [
@@ -1803,10 +1793,10 @@
"id": "bbe47670",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.109894Z",
"iopub.status.busy": "2025-04-03T19:32:51.109814Z",
"iopub.status.idle": "2025-04-03T19:32:51.124106Z",
"shell.execute_reply": "2025-04-03T19:32:51.123871Z"
"iopub.execute_input": "2026-02-02T23:39:31.035261Z",
"iopub.status.busy": "2026-02-02T23:39:31.035192Z",
"iopub.status.idle": "2026-02-02T23:39:31.050874Z",
"shell.execute_reply": "2026-02-02T23:39:31.050643Z"
}
},
"outputs": [
@@ -1979,10 +1969,10 @@
"id": "a1484d00",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.125356Z",
"iopub.status.busy": "2025-04-03T19:32:51.125276Z",
"iopub.status.idle": "2025-04-03T19:32:51.138960Z",
"shell.execute_reply": "2025-04-03T19:32:51.138745Z"
"iopub.execute_input": "2026-02-02T23:39:31.052042Z",
"iopub.status.busy": "2026-02-02T23:39:31.051970Z",
"iopub.status.idle": "2026-02-02T23:39:31.067211Z",
"shell.execute_reply": "2026-02-02T23:39:31.066979Z"
}
},
"outputs": [
@@ -2167,10 +2157,10 @@
"id": "46ac946c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.140138Z",
"iopub.status.busy": "2025-04-03T19:32:51.140067Z",
"iopub.status.idle": "2025-04-03T19:32:51.146004Z",
"shell.execute_reply": "2025-04-03T19:32:51.145771Z"
"iopub.execute_input": "2026-02-02T23:39:31.068412Z",
"iopub.status.busy": "2026-02-02T23:39:31.068335Z",
"iopub.status.idle": "2026-02-02T23:39:31.074305Z",
"shell.execute_reply": "2026-02-02T23:39:31.074088Z"
},
"lines_to_next_cell": 0
},
@@ -2299,10 +2289,10 @@
"id": "b626ecb9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.147247Z",
"iopub.status.busy": "2025-04-03T19:32:51.147171Z",
"iopub.status.idle": "2025-04-03T19:32:51.151571Z",
"shell.execute_reply": "2025-04-03T19:32:51.151341Z"
"iopub.execute_input": "2026-02-02T23:39:31.075380Z",
"iopub.status.busy": "2026-02-02T23:39:31.075309Z",
"iopub.status.idle": "2026-02-02T23:39:31.079549Z",
"shell.execute_reply": "2026-02-02T23:39:31.079349Z"
},
"lines_to_next_cell": 0
},
@@ -2332,10 +2322,10 @@
"id": "8bf77477",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.152822Z",
"iopub.status.busy": "2025-04-03T19:32:51.152716Z",
"iopub.status.idle": "2025-04-03T19:32:51.163070Z",
"shell.execute_reply": "2025-04-03T19:32:51.162825Z"
"iopub.execute_input": "2026-02-02T23:39:31.080739Z",
"iopub.status.busy": "2026-02-02T23:39:31.080668Z",
"iopub.status.idle": "2026-02-02T23:39:31.092282Z",
"shell.execute_reply": "2026-02-02T23:39:31.092056Z"
},
"lines_to_next_cell": 2
},
@@ -2440,10 +2430,10 @@
"id": "6289c3cb",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.164397Z",
"iopub.status.busy": "2025-04-03T19:32:51.164312Z",
"iopub.status.idle": "2025-04-03T19:32:51.175546Z",
"shell.execute_reply": "2025-04-03T19:32:51.175305Z"
"iopub.execute_input": "2026-02-02T23:39:31.093513Z",
"iopub.status.busy": "2026-02-02T23:39:31.093439Z",
"iopub.status.idle": "2026-02-02T23:39:31.104646Z",
"shell.execute_reply": "2026-02-02T23:39:31.104378Z"
},
"lines_to_next_cell": 0
},
@@ -2558,10 +2548,10 @@
"id": "b6542ac6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.176770Z",
"iopub.status.busy": "2025-04-03T19:32:51.176688Z",
"iopub.status.idle": "2025-04-03T19:32:51.180893Z",
"shell.execute_reply": "2025-04-03T19:32:51.180653Z"
"iopub.execute_input": "2026-02-02T23:39:31.105936Z",
"iopub.status.busy": "2026-02-02T23:39:31.105862Z",
"iopub.status.idle": "2026-02-02T23:39:31.111397Z",
"shell.execute_reply": "2026-02-02T23:39:31.111147Z"
},
"lines_to_next_cell": 0
},
@@ -2668,17 +2658,17 @@
"id": "8e4c6004",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:51.182118Z",
"iopub.status.busy": "2025-04-03T19:32:51.182029Z",
"iopub.status.idle": "2025-04-03T19:32:51.233426Z",
"shell.execute_reply": "2025-04-03T19:32:51.233183Z"
"iopub.execute_input": "2026-02-02T23:39:31.112521Z",
"iopub.status.busy": "2026-02-02T23:39:31.112440Z",
"iopub.status.idle": "2026-02-02T23:39:31.190330Z",
"shell.execute_reply": "2026-02-02T23:39:31.189998Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2724,10 +2714,10 @@
"id": "a83f4bd2",
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"execution": {
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@@ -2775,10 +2765,10 @@
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Ch04-classification-lab.Rmd
+2 -2
View File
@@ -13,11 +13,11 @@ jupyter:
# Logistic Regression, LDA, QDA, and KNN
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch04-classification-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch04-classification-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch04-classification-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch04-classification-lab.ipynb)
Ch04-classification-lab.ipynb
+329 -1542
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File diff suppressed because it is too large. Load diff
Ch05-resample-lab.Rmd
+2 -2
View File
@@ -13,11 +13,11 @@ jupyter:
# Cross-Validation and the Bootstrap
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch05-resample-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch05-resample-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch05-resample-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch05-resample-lab.ipynb)
In this lab, we explore the resampling techniques covered in this
Ch05-resample-lab.ipynb
+106 -106
View File
@@ -7,11 +7,11 @@
"source": [
"# Cross-Validation and the Bootstrap\n",
"\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch05-resample-lab.ipynb\">\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch05-resample-lab.ipynb\">\n",
"<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch05-resample-lab.ipynb)"
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch05-resample-lab.ipynb)"
]
},
{
@@ -32,10 +32,10 @@
"id": "f1deb5cc",
"metadata": {
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@@ -64,10 +64,10 @@
"id": "268c41b3",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.820788Z",
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"iopub.execute_input": "2026-02-02T23:39:39.123447Z",
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},
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@@ -108,10 +108,10 @@
"id": "22f44ae0",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.823864Z",
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"shell.execute_reply": "2026-02-02T23:39:39.135968Z"
}
},
"outputs": [],
@@ -136,10 +136,10 @@
"id": "0c32e917",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.830793Z",
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}
},
"outputs": [],
@@ -166,10 +166,10 @@
"id": "86ce4f85",
"metadata": {
"execution": {
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}
},
"outputs": [
@@ -210,10 +210,10 @@
"id": "50a66a97",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.841088Z",
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}
},
"outputs": [],
@@ -253,10 +253,10 @@
"id": "d49b6999",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.844166Z",
"iopub.status.busy": "2025-04-03T19:33:23.844091Z",
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"shell.execute_reply": "2026-02-02T23:39:39.167243Z"
}
},
"outputs": [
@@ -297,10 +297,10 @@
"id": "dac8bd54",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.857092Z",
"iopub.status.busy": "2025-04-03T19:33:23.857011Z",
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"iopub.execute_input": "2026-02-02T23:39:39.168726Z",
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}
},
"outputs": [
@@ -380,10 +380,10 @@
"id": "601ae443",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:23.869578Z",
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@@ -448,10 +448,10 @@
"id": "11226c85",
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"execution": {
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@@ -505,10 +505,10 @@
"id": "64b64d97",
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@@ -547,10 +547,10 @@
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@@ -613,10 +613,10 @@
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@@ -657,10 +657,10 @@
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@@ -731,10 +731,10 @@
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@@ -765,10 +765,10 @@
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@@ -804,10 +804,10 @@
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@@ -847,10 +847,10 @@
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@@ -892,10 +892,10 @@
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@@ -958,10 +958,10 @@
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@@ -993,10 +993,10 @@
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@@ -1026,10 +1026,10 @@
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@@ -1077,10 +1077,10 @@
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@@ -1127,10 +1127,10 @@
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@@ -1199,10 +1199,10 @@
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@@ -1242,10 +1242,10 @@
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Ch06-varselect-lab.Rmd
+17 -6
View File
@@ -1,23 +1,26 @@
---
jupyter:
jupytext:
cell_metadata_filter: -all
cell_metadata_filter: language,-all
formats: Rmd
main_language: python
text_representation:
extension: .Rmd
format_name: rmarkdown
format_version: '1.2'
jupytext_version: 1.19.1
kernelspec:
display_name: Python 3 (ipykernel)
language: python
name: python3
---
# Linear Models and Regularization Methods
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch06-varselect-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch06-varselect-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch06-varselect-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch06-varselect-lab.ipynb)
In this lab we implement many of the techniques discussed in this chapter.
@@ -39,7 +42,7 @@ from functools import partial
```
We again collect the new imports
needed for this lab. Readers will also have to have installed `l0bnb` using `pip install l0bnb`.
needed for this lab. Readers will have installed `l0bnb` when installing the requirements.
```{python}
from sklearn.pipeline import Pipeline
@@ -53,6 +56,14 @@ from l0bnb import fit_path
```
Using `skl.ElasticNet` to fit ridge regression
throws up many warnings. We will suppress them below by a call to `warnings.simplefilter()`.
```{python}
import warnings
warnings.simplefilter("ignore")
```
## Subset Selection Methods
Here we implement methods that reduce the number of parameters in a
model by restricting the model to a subset of the input variables.
@@ -368,7 +379,7 @@ estimates on the original scale, we must *unstandardize*
the coefficient estimates. The parameter
$\lambda$ in (\ref{Ch6:ridge}) and (\ref{Ch6:LASSO}) is called `alphas` in `sklearn`. In order to
be consistent with the rest of this chapter, we use `lambdas`
rather than `alphas` in what follows. {At the time of publication, ridge fits like the one in code chunk [22] issue unwarranted convergence warning messages; we expect these to disappear as this package matures.}
rather than `alphas` in what follows. {At the time of publication, ridge fits like the one in code chunk [23] issue unwarranted convergence warning messages; we suppressed these when we filtered the warnings above.}
```{python}
Xs = X - X.mean(0)[None,:]
Ch06-varselect-lab.ipynb
+187 -10446
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Ch07-nonlin-lab.Rmd
+2 -2
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@@ -13,11 +13,11 @@ jupyter:
# Non-Linear Modeling
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch07-nonlin-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch07-nonlin-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch07-nonlin-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch07-nonlin-lab.ipynb)
In this lab, we demonstrate some of the nonlinear models discussed in
Ch07-nonlin-lab.ipynb
+217 -281
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@@ -7,11 +7,11 @@
"source": [
"# Non-Linear Modeling\n",
"\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch07-nonlin-lab.ipynb\">\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch07-nonlin-lab.ipynb\">\n",
"<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch07-nonlin-lab.ipynb)"
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch07-nonlin-lab.ipynb)"
]
},
{
@@ -31,10 +31,10 @@
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@@ -65,10 +65,10 @@
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@@ -104,10 +104,10 @@
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@@ -134,10 +134,10 @@
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@@ -269,10 +269,10 @@
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@@ -304,10 +304,10 @@
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@@ -361,17 +361,17 @@
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{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -430,10 +430,10 @@
"id": "c338a92a",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.562604Z",
"iopub.status.busy": "2025-04-03T19:33:51.561921Z",
"iopub.status.idle": "2025-04-03T19:33:51.635689Z",
"shell.execute_reply": "2025-04-03T19:33:51.634613Z"
"iopub.execute_input": "2026-02-02T23:40:05.793488Z",
"iopub.status.busy": "2026-02-02T23:40:05.791036Z",
"iopub.status.idle": "2026-02-02T23:40:05.881585Z",
"shell.execute_reply": "2026-02-02T23:40:05.880105Z"
}
},
"outputs": [
@@ -570,10 +570,10 @@
"id": "a1f74b79",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.639833Z",
"iopub.status.busy": "2025-04-03T19:33:51.639168Z",
"iopub.status.idle": "2025-04-03T19:33:51.663992Z",
"shell.execute_reply": "2025-04-03T19:33:51.661163Z"
"iopub.execute_input": "2026-02-02T23:40:05.885672Z",
"iopub.status.busy": "2026-02-02T23:40:05.884933Z",
"iopub.status.idle": "2026-02-02T23:40:05.898439Z",
"shell.execute_reply": "2026-02-02T23:40:05.897738Z"
},
"lines_to_next_cell": 2
},
@@ -679,10 +679,10 @@
"id": "570892d1",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.670914Z",
"iopub.status.busy": "2025-04-03T19:33:51.669751Z",
"iopub.status.idle": "2025-04-03T19:33:51.675840Z",
"shell.execute_reply": "2025-04-03T19:33:51.674407Z"
"iopub.execute_input": "2026-02-02T23:40:05.901272Z",
"iopub.status.busy": "2026-02-02T23:40:05.901144Z",
"iopub.status.idle": "2026-02-02T23:40:05.905409Z",
"shell.execute_reply": "2026-02-02T23:40:05.904639Z"
},
"lines_to_next_cell": 2
},
@@ -720,10 +720,10 @@
"id": "3ff20916",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.681787Z",
"iopub.status.busy": "2025-04-03T19:33:51.681279Z",
"iopub.status.idle": "2025-04-03T19:33:51.737645Z",
"shell.execute_reply": "2025-04-03T19:33:51.735323Z"
"iopub.execute_input": "2026-02-02T23:40:05.911425Z",
"iopub.status.busy": "2026-02-02T23:40:05.909745Z",
"iopub.status.idle": "2026-02-02T23:40:05.957091Z",
"shell.execute_reply": "2026-02-02T23:40:05.956219Z"
},
"lines_to_next_cell": 2
},
@@ -830,10 +830,10 @@
"id": "2952bde3",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.742075Z",
"iopub.status.busy": "2025-04-03T19:33:51.741235Z",
"iopub.status.idle": "2025-04-03T19:33:51.786585Z",
"shell.execute_reply": "2025-04-03T19:33:51.784529Z"
"iopub.execute_input": "2026-02-02T23:40:05.965037Z",
"iopub.status.busy": "2026-02-02T23:40:05.964704Z",
"iopub.status.idle": "2026-02-02T23:40:06.001971Z",
"shell.execute_reply": "2026-02-02T23:40:05.999012Z"
},
"lines_to_next_cell": 2
},
@@ -943,10 +943,10 @@
"id": "c999b609",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.795007Z",
"iopub.status.busy": "2025-04-03T19:33:51.794240Z",
"iopub.status.idle": "2025-04-03T19:33:51.802485Z",
"shell.execute_reply": "2025-04-03T19:33:51.801339Z"
"iopub.execute_input": "2026-02-02T23:40:06.019403Z",
"iopub.status.busy": "2026-02-02T23:40:06.018964Z",
"iopub.status.idle": "2026-02-02T23:40:06.037704Z",
"shell.execute_reply": "2026-02-02T23:40:06.036171Z"
}
},
"outputs": [],
@@ -970,17 +970,17 @@
"id": "5f18a110",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.815260Z",
"iopub.status.busy": "2025-04-03T19:33:51.814446Z",
"iopub.status.idle": "2025-04-03T19:33:51.889477Z",
"shell.execute_reply": "2025-04-03T19:33:51.888860Z"
"iopub.execute_input": "2026-02-02T23:40:06.043165Z",
"iopub.status.busy": "2026-02-02T23:40:06.042103Z",
"iopub.status.idle": "2026-02-02T23:40:06.198945Z",
"shell.execute_reply": "2026-02-02T23:40:06.195028Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1035,10 +1035,10 @@
"id": "62e053ea",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.903456Z",
"iopub.status.busy": "2025-04-03T19:33:51.902924Z",
"iopub.status.idle": "2025-04-03T19:33:51.931633Z",
"shell.execute_reply": "2025-04-03T19:33:51.931013Z"
"iopub.execute_input": "2026-02-02T23:40:06.219759Z",
"iopub.status.busy": "2026-02-02T23:40:06.219144Z",
"iopub.status.idle": "2026-02-02T23:40:06.237765Z",
"shell.execute_reply": "2026-02-02T23:40:06.236959Z"
},
"lines_to_next_cell": 2
},
@@ -1164,10 +1164,10 @@
"id": "f032f577",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.941994Z",
"iopub.status.busy": "2025-04-03T19:33:51.941511Z",
"iopub.status.idle": "2025-04-03T19:33:51.954506Z",
"shell.execute_reply": "2025-04-03T19:33:51.952472Z"
"iopub.execute_input": "2026-02-02T23:40:06.242903Z",
"iopub.status.busy": "2026-02-02T23:40:06.242239Z",
"iopub.status.idle": "2026-02-02T23:40:06.258037Z",
"shell.execute_reply": "2026-02-02T23:40:06.256459Z"
},
"lines_to_next_cell": 0
},
@@ -1207,10 +1207,10 @@
"id": "c3c38823",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:51.964142Z",
"iopub.status.busy": "2025-04-03T19:33:51.963489Z",
"iopub.status.idle": "2025-04-03T19:33:51.997785Z",
"shell.execute_reply": "2025-04-03T19:33:51.995701Z"
"iopub.execute_input": "2026-02-02T23:40:06.263960Z",
"iopub.status.busy": "2026-02-02T23:40:06.263438Z",
"iopub.status.idle": "2026-02-02T23:40:06.339138Z",
"shell.execute_reply": "2026-02-02T23:40:06.338334Z"
},
"lines_to_next_cell": 0
},
@@ -1333,10 +1333,10 @@
"id": "d01c2c26",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.016425Z",
"iopub.status.busy": "2025-04-03T19:33:52.015784Z",
"iopub.status.idle": "2025-04-03T19:33:52.050518Z",
"shell.execute_reply": "2025-04-03T19:33:52.049543Z"
"iopub.execute_input": "2026-02-02T23:40:06.344840Z",
"iopub.status.busy": "2026-02-02T23:40:06.343158Z",
"iopub.status.idle": "2026-02-02T23:40:06.376418Z",
"shell.execute_reply": "2026-02-02T23:40:06.375567Z"
}
},
"outputs": [
@@ -1469,10 +1469,10 @@
"id": "672d44ae",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.061323Z",
"iopub.status.busy": "2025-04-03T19:33:52.060825Z",
"iopub.status.idle": "2025-04-03T19:33:52.068372Z",
"shell.execute_reply": "2025-04-03T19:33:52.067421Z"
"iopub.execute_input": "2026-02-02T23:40:06.381695Z",
"iopub.status.busy": "2026-02-02T23:40:06.380174Z",
"iopub.status.idle": "2026-02-02T23:40:06.396405Z",
"shell.execute_reply": "2026-02-02T23:40:06.389907Z"
},
"lines_to_next_cell": 0
},
@@ -1514,10 +1514,10 @@
"id": "4a3f93ee",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.072307Z",
"iopub.status.busy": "2025-04-03T19:33:52.071691Z",
"iopub.status.idle": "2025-04-03T19:33:52.108285Z",
"shell.execute_reply": "2025-04-03T19:33:52.106248Z"
"iopub.execute_input": "2026-02-02T23:40:06.408063Z",
"iopub.status.busy": "2026-02-02T23:40:06.407772Z",
"iopub.status.idle": "2026-02-02T23:40:06.442771Z",
"shell.execute_reply": "2026-02-02T23:40:06.440472Z"
},
"lines_to_next_cell": 0
},
@@ -1648,10 +1648,10 @@
"id": "bd2b4215",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.111583Z",
"iopub.status.busy": "2025-04-03T19:33:52.111100Z",
"iopub.status.idle": "2025-04-03T19:33:52.147048Z",
"shell.execute_reply": "2025-04-03T19:33:52.146152Z"
"iopub.execute_input": "2026-02-02T23:40:06.448105Z",
"iopub.status.busy": "2026-02-02T23:40:06.447658Z",
"iopub.status.idle": "2026-02-02T23:40:06.488457Z",
"shell.execute_reply": "2026-02-02T23:40:06.487318Z"
},
"lines_to_next_cell": 0
},
@@ -1765,16 +1765,16 @@
"id": "9162a058",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.151839Z",
"iopub.status.busy": "2025-04-03T19:33:52.150012Z",
"iopub.status.idle": "2025-04-03T19:33:52.224198Z",
"shell.execute_reply": "2025-04-03T19:33:52.223407Z"
"iopub.execute_input": "2026-02-02T23:40:06.492041Z",
"iopub.status.busy": "2026-02-02T23:40:06.491469Z",
"iopub.status.idle": "2026-02-02T23:40:06.634284Z",
"shell.execute_reply": "2026-02-02T23:40:06.633462Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1813,10 +1813,10 @@
"id": "86ff9343",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.237478Z",
"iopub.status.busy": "2025-04-03T19:33:52.236869Z",
"iopub.status.idle": "2025-04-03T19:33:52.297555Z",
"shell.execute_reply": "2025-04-03T19:33:52.296760Z"
"iopub.execute_input": "2026-02-02T23:40:06.644991Z",
"iopub.status.busy": "2026-02-02T23:40:06.644517Z",
"iopub.status.idle": "2026-02-02T23:40:06.699298Z",
"shell.execute_reply": "2026-02-02T23:40:06.698442Z"
}
},
"outputs": [
@@ -1859,16 +1859,16 @@
"id": "44812968",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.309060Z",
"iopub.status.busy": "2025-04-03T19:33:52.308243Z",
"iopub.status.idle": "2025-04-03T19:33:52.649713Z",
"shell.execute_reply": "2025-04-03T19:33:52.647160Z"
"iopub.execute_input": "2026-02-02T23:40:06.704453Z",
"iopub.status.busy": "2026-02-02T23:40:06.703915Z",
"iopub.status.idle": "2026-02-02T23:40:07.048339Z",
"shell.execute_reply": "2026-02-02T23:40:07.045612Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1905,10 +1905,10 @@
"id": "968e1e42",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:52.655836Z",
"iopub.status.busy": "2025-04-03T19:33:52.655411Z",
"iopub.status.idle": "2025-04-03T19:33:53.201562Z",
"shell.execute_reply": "2025-04-03T19:33:53.200247Z"
"iopub.execute_input": "2026-02-02T23:40:07.054538Z",
"iopub.status.busy": "2026-02-02T23:40:07.053319Z",
"iopub.status.idle": "2026-02-02T23:40:07.764145Z",
"shell.execute_reply": "2026-02-02T23:40:07.758170Z"
}
},
"outputs": [
@@ -1916,76 +1916,12 @@
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;255;0;0m 0%\u001b[39m \u001b[38;2;255;0;0m(0 of 11)\u001b[39m | | Elapsed Time: 0:00:00 ETA: --:--:--"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;255;105;0m 18%\u001b[39m \u001b[38;2;255;105;0m(2 of 11)\u001b[39m |#### | Elapsed Time: 0:00:00 ETA: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;255;156;0m 36%\u001b[39m \u001b[38;2;255;156;0m(4 of 11)\u001b[39m |######### | Elapsed Time: 0:00:00 ETA: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;255;189;0m 45%\u001b[39m \u001b[38;2;255;189;0m(5 of 11)\u001b[39m |########### | Elapsed Time: 0:00:00 ETA: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;236;255;0m 63%\u001b[39m \u001b[38;2;236;255;0m(7 of 11)\u001b[39m |############### | Elapsed Time: 0:00:00 ETA: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;185;255;0m 81%\u001b[39m \u001b[38;2;185;255;0m(9 of 11)\u001b[39m |#################### | Elapsed Time: 0:00:00 ETA: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;160;255;0m 90%\u001b[39m \u001b[38;2;160;255;0m(10 of 11)\u001b[39m |##################### | Elapsed Time: 0:00:00 ETA: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\r",
"\u001b[38;2;0;255;0m100%\u001b[39m \u001b[38;2;0;255;0m(11 of 11)\u001b[39m |########################| Elapsed Time: 0:00:00 Time: 0:00:00"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
"100% (11 of 11) |########################| Elapsed Time: 0:00:00 Time: 0:00:00\n"
]
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2024,10 +1960,10 @@
"id": "891e3b75",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.212269Z",
"iopub.status.busy": "2025-04-03T19:33:53.211860Z",
"iopub.status.idle": "2025-04-03T19:33:53.259372Z",
"shell.execute_reply": "2025-04-03T19:33:53.257058Z"
"iopub.execute_input": "2026-02-02T23:40:07.776251Z",
"iopub.status.busy": "2026-02-02T23:40:07.775494Z",
"iopub.status.idle": "2026-02-02T23:40:07.849554Z",
"shell.execute_reply": "2026-02-02T23:40:07.848496Z"
},
"lines_to_next_cell": 2
},
@@ -2066,16 +2002,16 @@
"id": "54715029",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.263753Z",
"iopub.status.busy": "2025-04-03T19:33:53.263235Z",
"iopub.status.idle": "2025-04-03T19:33:53.665292Z",
"shell.execute_reply": "2025-04-03T19:33:53.663172Z"
"iopub.execute_input": "2026-02-02T23:40:07.859355Z",
"iopub.status.busy": "2026-02-02T23:40:07.856623Z",
"iopub.status.idle": "2026-02-02T23:40:08.242689Z",
"shell.execute_reply": "2026-02-02T23:40:08.238652Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2128,10 +2064,10 @@
"id": "b3cd8b66",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.669951Z",
"iopub.status.busy": "2025-04-03T19:33:53.669276Z",
"iopub.status.idle": "2025-04-03T19:33:53.713659Z",
"shell.execute_reply": "2025-04-03T19:33:53.710699Z"
"iopub.execute_input": "2026-02-02T23:40:08.250890Z",
"iopub.status.busy": "2026-02-02T23:40:08.250313Z",
"iopub.status.idle": "2026-02-02T23:40:08.271867Z",
"shell.execute_reply": "2026-02-02T23:40:08.270944Z"
},
"lines_to_next_cell": 0
},
@@ -2167,17 +2103,17 @@
"id": "ea8d6bc5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.717419Z",
"iopub.status.busy": "2025-04-03T19:33:53.717296Z",
"iopub.status.idle": "2025-04-03T19:33:53.778191Z",
"shell.execute_reply": "2025-04-03T19:33:53.776227Z"
"iopub.execute_input": "2026-02-02T23:40:08.279079Z",
"iopub.status.busy": "2026-02-02T23:40:08.276832Z",
"iopub.status.idle": "2026-02-02T23:40:08.473171Z",
"shell.execute_reply": "2026-02-02T23:40:08.472311Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2230,16 +2166,16 @@
"id": "812a47a1",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.781510Z",
"iopub.status.busy": "2025-04-03T19:33:53.780977Z",
"iopub.status.idle": "2025-04-03T19:33:53.897521Z",
"shell.execute_reply": "2025-04-03T19:33:53.894935Z"
"iopub.execute_input": "2026-02-02T23:40:08.477593Z",
"iopub.status.busy": "2026-02-02T23:40:08.477299Z",
"iopub.status.idle": "2026-02-02T23:40:08.585625Z",
"shell.execute_reply": "2026-02-02T23:40:08.585355Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2291,10 +2227,10 @@
"id": "88ff3def",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.903332Z",
"iopub.status.busy": "2025-04-03T19:33:53.902411Z",
"iopub.status.idle": "2025-04-03T19:33:53.948364Z",
"shell.execute_reply": "2025-04-03T19:33:53.947139Z"
"iopub.execute_input": "2026-02-02T23:40:08.586993Z",
"iopub.status.busy": "2026-02-02T23:40:08.586890Z",
"iopub.status.idle": "2026-02-02T23:40:08.639073Z",
"shell.execute_reply": "2026-02-02T23:40:08.636999Z"
},
"lines_to_next_cell": 0
},
@@ -2328,16 +2264,16 @@
"id": "29dbc933",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:53.951460Z",
"iopub.status.busy": "2025-04-03T19:33:53.951209Z",
"iopub.status.idle": "2025-04-03T19:33:54.028760Z",
"shell.execute_reply": "2025-04-03T19:33:54.025536Z"
"iopub.execute_input": "2026-02-02T23:40:08.649833Z",
"iopub.status.busy": "2026-02-02T23:40:08.649413Z",
"iopub.status.idle": "2026-02-02T23:40:08.786665Z",
"shell.execute_reply": "2026-02-02T23:40:08.783766Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2371,10 +2307,10 @@
"id": "cdb535b5",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.037314Z",
"iopub.status.busy": "2025-04-03T19:33:54.036928Z",
"iopub.status.idle": "2025-04-03T19:33:54.091522Z",
"shell.execute_reply": "2025-04-03T19:33:54.087570Z"
"iopub.execute_input": "2026-02-02T23:40:08.795057Z",
"iopub.status.busy": "2026-02-02T23:40:08.794070Z",
"iopub.status.idle": "2026-02-02T23:40:08.852216Z",
"shell.execute_reply": "2026-02-02T23:40:08.851194Z"
},
"lines_to_next_cell": 0
},
@@ -2404,10 +2340,10 @@
"id": "2acadc27",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.097247Z",
"iopub.status.busy": "2025-04-03T19:33:54.096681Z",
"iopub.status.idle": "2025-04-03T19:33:54.164314Z",
"shell.execute_reply": "2025-04-03T19:33:54.163688Z"
"iopub.execute_input": "2026-02-02T23:40:08.862001Z",
"iopub.status.busy": "2026-02-02T23:40:08.861499Z",
"iopub.status.idle": "2026-02-02T23:40:08.997608Z",
"shell.execute_reply": "2026-02-02T23:40:08.995381Z"
},
"lines_to_next_cell": 0
},
@@ -2424,7 +2360,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAq8AAALFCAYAAADtDgqhAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8g+/7EAAAACXBIWXMAAA9hAAAPYQGoP6dpAACwSElEQVR4nOzdd3gUVRcG8HfTAyQhlAChhS5I7wJSBOlIBxGposBHUUQQkN6biEgTpCO99947oaP0Jh2kJCSE1Pv9cc2SZGc2u8lmtuT9Pc8+kLmzm5O2e/bOvefohBACRERERER2wMnaARARERERmYrJKxERERHZDSavRERERGQ3mLwSERERkd1g8kpEREREdoPJKxERERHZDSavRERERGQ3mLwSERERkd1g8kpEREREdoPJK9ml4cOHQ6fTQafTpdjnqF69OnQ6HapXr55inwMA7t69q/9aFi5cmKKfK7U5cOCA/nt74MABa4dD/4mOjsavv/6K8uXLw9vbW/8zatKkibVDIyI7wOTVgcV94U54S5MmDXLnzo0mTZpg2bJliIqKsna4RJRKtGnTBt999x1Onz6NN2/eWDscIrIzTF5TqbCwMPzzzz/YuHEj2rZti0qVKuHJkydWjWnhwoX65Pru3btWjYWIUsaxY8ewevVqAECDBg2we/duXLx4EZcuXcK0adOsHB0R2QMXawdA2ujevTv+97//6T8OCQlBYGAgfv75Z9y9exenT59G48aNceLEiRS9FG8pw4cPx/Dhw60dBhGZac+ePQAAZ2dnLFu2DN7e3laOiIjsDZPXVMLPzw9FixaNd6xixYpo27Ytypcvj5s3b+LUqVPYsmULGjVqZKUoicjRPXz4EACQJUsWJq5ElCRcNpDK+fr6YuDAgfqPd+zYYcVoiMjRhYeHAwBcXV2tHAkR2Ssmr4Ty5cvr/3/v3j39/0NDQ7Fy5Up06dIFJUuWhI+PD1xdXZE5c2ZUq1YNkydPRkhIiNHHjl3DGnuJf9++fWjZsiVy5swJV1dXBAQE6DeWderUSX+/PHnyGGwyi7tbPLFqAxEREdi8eTN69uyJcuXKwdfXF66ursiYMSMqVKiA4cOH499//03Cd8t80dHRmDlzJipUqABvb2/4+PigdOnSmDx5sv6F3FQbNmxAy5YtkStXLnh4eCB9+vQoW7YsRowYgVevXqner2PHjtDpdAgICAAgZ7++//57FCxYEGnSpEHmzJnRoEEDk9+8BAUFYdy4cahcuTIyZ84MNzc3ZMuWDY0aNcKaNWsghFC9b8LfidOnT6NNmzbIkSMH3N3dkT17drRr1w5XrlxJNI6wsDCMHTsWJUqUQNq0aZExY0ZUrlwZc+fORUxMjElfCyB/RosWLULDhg3h7+8Pd3d3ZMyYEVWqVMGUKVMQFhamet+EVSliv7f58+eHp6cnMmbMiDp16mD79u0mxfL8+XOMHDkSlStXhp+fH1xdXeHr64sKFSqgf//+uHjxoup93717h+nTp6NmzZrImjUr3Nzc4Ofnh1q1amHevHkW25h56dIlfPPNNyhQoADSpEkDLy8vfPjhh+jTp4/qevXYn/uiRYsAyOeahH/jpoiMjETWrFmh0+lQt27dRM+/fPmy/vEnTpyoeM6TJ0/w008/oWzZssiQIQPc3d2RM2dOtGrVSr/MQc2rV6+wYMECfPnllyhSpAjSpUsHNzc3ZM2aFXXq1MGcOXMQERGhen+laiPr1q1D/fr14e/vDxcXlyRXPHn+/DkGDx6MUqVKIX369PDw8EBAQADatWuHI0eOGL1vQEAAdDodOnbsCAC4du0avv76awQEBMDd3R1ZsmRB06ZNceLEiSTFBgA9e/aETqdDtmzZFMfjfm+cnJzw8uVLg3OioqLg5eUFnU6HAQMGGIyfOHECgwcPRvXq1fV/E97e3ihSpAi6d++Ov//+26RY//nnH3Tv3h158uSBh4cH/P390aRJE+zfvx+A6RVwkvPcSXEIclj79+8XAAQAMWzYMNXzrl69qj+vbt26+uPVqlXTH1e75cmTR1y5ckX1seN+/kGDBhncP3fu3PHiNHbbv3+//nGHDRumP66kQ4cOiT5exowZxZEjR1Rjj/36q1WrpnpOYt68eSM+/vhj1RhKly4tzp49q/94wYIFio/z8uVL8cknnxj9evz8/MTx48eNfj9y584tTp8+Lfz8/FQf5/vvvzf6Ne3Zs0dkzJjRaCz169cXb968Ubx/3N+JGTNmCBcXF8XHSJMmjTh48KBqHI8fPxaFCxdWjaFOnTpi586dir8/cd27d0+UKFHC6NeTP39+ce3aNcX7x/09OXLkiMiUKZPq40yaNMno93bp0qUibdq0RmPJnTu34n3Pnz8vcufObfS+5cqVE0+ePDEaQ2LGjh0rnJycVD+Hu7u7WLRokcH9TPkbN1W/fv0EAOHk5CQePHhg9Nw+ffoIAMLFxUU8fvzYYNyU7/lXX30lIiMjFR8/se85AFGqVCnFzy2EEHfu3NGfN3/+fNGuXTuD+yflOWjnzp3C29vbaFw9evQQ0dHRRr+uDh06iHXr1ok0adIoPoazs7NYsWKF2fEJIcSqVav0j6P0OrJw4cJ4n2v9+vUG55w4cUI/vn379nhjCxYsSPRn4+zsLGbMmGE0zr1794p06dIp3l+n04kxY8Yk+pokRPKfO+k9Jq8OzNTkdfXq1frzOnfurD9euXJlUaxYMfHTTz+J9evXi5MnT4oTJ06IlStXis8//1z/AlaoUCERFham+Nixj1usWDH9v/PnzxenTp0SBw8eFL/++qsICQkRly5dEqNHj9afv3PnTnHp0qV4t5CQEP3jJvZE0bZtW5E3b17Rt29fsXLlSnH8+HFx+vRpsWbNGtGtWzfh5uYmAIjMmTOLp0+fKj6GJZLXxo0b6+MsX768WL58uQgMDBRbt24VLVu21CcUsecoJa/v3r0TpUuX1j/RtmvXTixfvlycOHFCHD58WIwZM0b/hOjr6yvu3r1r8BixyWvmzJlFQECAcHd3FwMGDBCHDh0SJ0+eFNOmTRPZsmXTxzF16lTFr+fIkSPC1dVVABBZsmQRo0ePFps3bxZnzpwRmzdvFl9++aX+MZo1a6b4GLHjFStWFE5OTqJEiRJi/vz54vTp0+LQoUOiT58++t+tXLlyifDwcIPHiIyMFGXKlNE/Vu3atcX69etFYGCgWLdunahVq5bB91Ypef33339Fzpw59UlXz549xerVq8Xp06fF/v37xcCBA/Uv2nnz5hWvX782eIzY35OCBQuKTJkyCT8/PzF+/Hhx5MgRcerUKTFlyhSRPn16fQJ1+fJlxe/L4sWL9bF6eHiIXr16iW3btomzZ8+KQ4cOienTp4vatWuLPHnyGNz3xo0bwsfHRwAQ3t7eYuDAgfrvx86dO0WPHj30bxIqVKggIiIiFGNIzIwZM/QxZs6cWUyePFkcP35cHDlyRAwfPlyfBOp0OrF169Z49439O479m/D39zf4GzfVtWvX9HGMHTtW9byIiAiROXNmAUA0atTIYHzlypVCp9Ppf75TpkwRO3bsEGfOnBFr164V9evX13+ePn36KH6OHDlyiAoVKohRo0aJLVu2iNOnT4ujR4+KpUuXirp16yaagMZNXosXLy4AiI8//lgsW7ZMBAYGij179og//vjD5O+NEEKcO3dO/xzn6uoq+vTpI/bv3y9OnTolfv/9d5EnTx795+zfv7/iY8Qmr6VLlxYeHh4iT548Yvr06eLEiRPi+PHjYvjw4cLDw0P/O/fs2TOzYhRCiKdPn+rjmDVrlsF4x44d4yV23377rcE548eP1/9tBQcHxxubO3eu8PX1FR07dhTz588Xhw8fFmfPnhVbtmwRI0eO1L/R1Ol0Yu/evYox3rp1S/977eLiInr16iX27t0rTp8+LRYsWCCKFCmi/7sy9ppkiedOeo/JqwMzJXmNjIwUFStW1J+3ePFi/dj169eNPv7u3bv1SYbak2vcJ56aNWuKd+/eqT5e3HfJd+7cMfq5E0teb968KWJiYlTvf/HiRf076cGDByuek9zkdcuWLfHeTSvN3IwYMSLe90gpeY2dsU6fPr0IDAxU/Fx3797VJ59ffPGFwXjcmWhXV1fFGc2HDx+KHDlyCAAibdq0Bi9GERERIiAgQAByhj40NFQxljlz5ug/165duwzGE84yKCWncd/IrFu3zmB8+vTp+vFvvvlGMY7OnTvH+1xKyesXX3whADmbefv2bcXHOXv2rP7Fa9CgQQbjca9Q5M6dW3Em8PDhw/okqXfv3gbjjx490ifJfn5+RhO5f/75x+BYpUqVBCBn+J4/f654v+3bt+v/XufMmaP6+GqePXumj9Hf318xjrjfq+zZsysmyXGvAiRH7BWNggULqp6zbt06/c8m4azd8+fP9Ql/586dVWdWY//+nJycxNWrVw3GE3uenD9/vj6GPXv2GIzHTV4BiPbt2xt97jJF7Js2Z2dnsXPnToPxly9f6pMuJycnxTdUcWeUy5QpI4KCggzOWbp0qf6cKVOmJCnW2KsnrVu3NhiLTbIbNWokAIgSJUoYnFOvXj0ByMmBhB48eKD6PCWEEK9fv9a/YahSpYriOU2aNFH9HRJCiNDQUFG+fPl4P8OELPXcSe8xeXVgxpLXkJAQceDAAVG9evV4L7zGkkslsX/YDRs2VByPfWwnJ6dEE1JLJq+m+O677wQAUbRoUcXx5CavsbM27u7u4uHDh4rnREdHi6JFi6omr2/evNG/wP72229GP9/MmTP1yWncWWoh4ievPXv2VH2MlStX6s9LeIk7dmbQw8Mj0VmW2CdzpUQ69vE9PDxUZ72Dg4P1M0dKM16xL7xZsmRRfSF48+aNftZNKXm9c+eOcHZ2FgDE5s2bjX49/fv31ydtCcVNXjdt2qT6GLFvEkuVKmUwNnDgQP1jbNiwwWgsCR06dEh/34sXLxo9t1WrVgKAqFSpklmLine truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2457,16 +2393,16 @@
"id": "a2b8e481",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.167414Z",
"iopub.status.busy": "2025-04-03T19:33:54.167155Z",
"iopub.status.idle": "2025-04-03T19:33:54.249548Z",
"shell.execute_reply": "2025-04-03T19:33:54.246730Z"
"iopub.execute_input": "2026-02-02T23:40:09.002296Z",
"iopub.status.busy": "2026-02-02T23:40:09.001315Z",
"iopub.status.idle": "2026-02-02T23:40:09.149447Z",
"shell.execute_reply": "2026-02-02T23:40:09.149182Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2504,10 +2440,10 @@
"id": "1a76b516",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.253007Z",
"iopub.status.busy": "2025-04-03T19:33:54.252338Z",
"iopub.status.idle": "2025-04-03T19:33:54.343941Z",
"shell.execute_reply": "2025-04-03T19:33:54.340978Z"
"iopub.execute_input": "2026-02-02T23:40:09.150850Z",
"iopub.status.busy": "2026-02-02T23:40:09.150766Z",
"iopub.status.idle": "2026-02-02T23:40:09.195213Z",
"shell.execute_reply": "2026-02-02T23:40:09.194439Z"
}
},
"outputs": [
@@ -2551,10 +2487,10 @@
"id": "7a68bf04",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.348524Z",
"iopub.status.busy": "2025-04-03T19:33:54.348254Z",
"iopub.status.idle": "2025-04-03T19:33:54.360318Z",
"shell.execute_reply": "2025-04-03T19:33:54.359165Z"
"iopub.execute_input": "2026-02-02T23:40:09.200853Z",
"iopub.status.busy": "2026-02-02T23:40:09.200508Z",
"iopub.status.idle": "2026-02-02T23:40:09.215341Z",
"shell.execute_reply": "2026-02-02T23:40:09.214543Z"
},
"lines_to_next_cell": 0
},
@@ -2658,10 +2594,10 @@
"id": "a05df53b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.364260Z",
"iopub.status.busy": "2025-04-03T19:33:54.363536Z",
"iopub.status.idle": "2025-04-03T19:33:54.409320Z",
"shell.execute_reply": "2025-04-03T19:33:54.408390Z"
"iopub.execute_input": "2026-02-02T23:40:09.222409Z",
"iopub.status.busy": "2026-02-02T23:40:09.221994Z",
"iopub.status.idle": "2026-02-02T23:40:09.293114Z",
"shell.execute_reply": "2026-02-02T23:40:09.292333Z"
}
},
"outputs": [
@@ -2768,10 +2704,10 @@
"id": "ee9db82c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.413076Z",
"iopub.status.busy": "2025-04-03T19:33:54.412575Z",
"iopub.status.idle": "2025-04-03T19:33:54.417902Z",
"shell.execute_reply": "2025-04-03T19:33:54.416893Z"
"iopub.execute_input": "2026-02-02T23:40:09.297734Z",
"iopub.status.busy": "2026-02-02T23:40:09.297612Z",
"iopub.status.idle": "2026-02-02T23:40:09.302598Z",
"shell.execute_reply": "2026-02-02T23:40:09.300695Z"
}
},
"outputs": [
@@ -2810,7 +2746,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70598/2135516388.py:1: UserWarning: KNOWN BUG: p-values computed in this summary are likely much smaller than they should be. \n",
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_37174/2135516388.py:1: UserWarning: KNOWN BUG: p-values computed in this summary are likely much smaller than they should be. \n",
" \n",
"Please do not make inferences based on these values! \n",
"\n",
@@ -2841,10 +2777,10 @@
"id": "cf0a024d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.424651Z",
"iopub.status.busy": "2025-04-03T19:33:54.423895Z",
"iopub.status.idle": "2025-04-03T19:33:54.439571Z",
"shell.execute_reply": "2025-04-03T19:33:54.438937Z"
"iopub.execute_input": "2026-02-02T23:40:09.307200Z",
"iopub.status.busy": "2026-02-02T23:40:09.306890Z",
"iopub.status.idle": "2026-02-02T23:40:09.331076Z",
"shell.execute_reply": "2026-02-02T23:40:09.323180Z"
}
},
"outputs": [],
@@ -2867,10 +2803,10 @@
"id": "0fe9f031",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.451992Z",
"iopub.status.busy": "2025-04-03T19:33:54.451137Z",
"iopub.status.idle": "2025-04-03T19:33:54.849000Z",
"shell.execute_reply": "2025-04-03T19:33:54.847284Z"
"iopub.execute_input": "2026-02-02T23:40:09.341654Z",
"iopub.status.busy": "2026-02-02T23:40:09.339837Z",
"iopub.status.idle": "2026-02-02T23:40:09.494967Z",
"shell.execute_reply": "2026-02-02T23:40:09.490916Z"
},
"lines_to_next_cell": 2
},
@@ -2901,17 +2837,17 @@
"id": "bdc73505",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.855349Z",
"iopub.status.busy": "2025-04-03T19:33:54.853647Z",
"iopub.status.idle": "2025-04-03T19:33:54.928284Z",
"shell.execute_reply": "2025-04-03T19:33:54.926859Z"
"iopub.execute_input": "2026-02-02T23:40:09.504438Z",
"iopub.status.busy": "2026-02-02T23:40:09.504038Z",
"iopub.status.idle": "2026-02-02T23:40:09.666427Z",
"shell.execute_reply": "2026-02-02T23:40:09.664475Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2945,10 +2881,10 @@
"id": "44f57a30",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.932765Z",
"iopub.status.busy": "2025-04-03T19:33:54.931894Z",
"iopub.status.idle": "2025-04-03T19:33:54.954335Z",
"shell.execute_reply": "2025-04-03T19:33:54.949457Z"
"iopub.execute_input": "2026-02-02T23:40:09.674786Z",
"iopub.status.busy": "2026-02-02T23:40:09.672927Z",
"iopub.status.idle": "2026-02-02T23:40:09.742669Z",
"shell.execute_reply": "2026-02-02T23:40:09.741650Z"
},
"lines_to_next_cell": 0
},
@@ -3054,10 +2990,10 @@
"id": "3b061ffd",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.958044Z",
"iopub.status.busy": "2025-04-03T19:33:54.957514Z",
"iopub.status.idle": "2025-04-03T19:33:54.965133Z",
"shell.execute_reply": "2025-04-03T19:33:54.964174Z"
"iopub.execute_input": "2026-02-02T23:40:09.744906Z",
"iopub.status.busy": "2026-02-02T23:40:09.744805Z",
"iopub.status.idle": "2026-02-02T23:40:09.747571Z",
"shell.execute_reply": "2026-02-02T23:40:09.747335Z"
},
"lines_to_next_cell": 0
},
@@ -3088,10 +3024,10 @@
"id": "220e26ac",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:54.969033Z",
"iopub.status.busy": "2025-04-03T19:33:54.967633Z",
"iopub.status.idle": "2025-04-03T19:33:55.092228Z",
"shell.execute_reply": "2025-04-03T19:33:55.089007Z"
"iopub.execute_input": "2026-02-02T23:40:09.749101Z",
"iopub.status.busy": "2026-02-02T23:40:09.748940Z",
"iopub.status.idle": "2026-02-02T23:40:09.810234Z",
"shell.execute_reply": "2026-02-02T23:40:09.809459Z"
},
"lines_to_next_cell": 2
},
@@ -3131,16 +3067,16 @@
"id": "94209d95",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:55.095854Z",
"iopub.status.busy": "2025-04-03T19:33:55.095223Z",
"iopub.status.idle": "2025-04-03T19:33:55.148813Z",
"shell.execute_reply": "2025-04-03T19:33:55.147907Z"
"iopub.execute_input": "2026-02-02T23:40:09.815307Z",
"iopub.status.busy": "2026-02-02T23:40:09.814851Z",
"iopub.status.idle": "2026-02-02T23:40:09.940943Z",
"shell.execute_reply": "2026-02-02T23:40:09.938255Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -3165,16 +3101,16 @@
"id": "b86a257f",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:55.152362Z",
"iopub.status.busy": "2025-04-03T19:33:55.151749Z",
"iopub.status.idle": "2025-04-03T19:33:55.224762Z",
"shell.execute_reply": "2025-04-03T19:33:55.224034Z"
"iopub.execute_input": "2026-02-02T23:40:09.946054Z",
"iopub.status.busy": "2026-02-02T23:40:09.945766Z",
"iopub.status.idle": "2026-02-02T23:40:10.067121Z",
"shell.execute_reply": "2026-02-02T23:40:10.042718Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -3198,17 +3134,17 @@
"id": "075082df",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:55.228948Z",
"iopub.status.busy": "2025-04-03T19:33:55.228423Z",
"iopub.status.idle": "2025-04-03T19:33:55.297977Z",
"shell.execute_reply": "2025-04-03T19:33:55.296769Z"
"iopub.execute_input": "2026-02-02T23:40:10.071915Z",
"iopub.status.busy": "2026-02-02T23:40:10.071795Z",
"iopub.status.idle": "2026-02-02T23:40:10.157549Z",
"shell.execute_reply": "2026-02-02T23:40:10.157211Z"
},
"lines_to_next_cell": 2
},
"outputs": [
{
"data": {
"image/png": 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truncated
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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -3246,17 +3182,17 @@
"id": "ecef97c8",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:33:55.301548Z",
"iopub.status.busy": "2025-04-03T19:33:55.300921Z",
"iopub.status.idle": "2025-04-03T19:33:55.392273Z",
"shell.execute_reply": "2025-04-03T19:33:55.391971Z"
"iopub.execute_input": "2026-02-02T23:40:10.158964Z",
"iopub.status.busy": "2026-02-02T23:40:10.158870Z",
"iopub.status.idle": "2026-02-02T23:40:10.273331Z",
"shell.execute_reply": "2026-02-02T23:40:10.272820Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -3309,7 +3245,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
"version": "3.11.4"
}
},
"nbformat": 4,
Ch08-baggboost-lab.Rmd
+2 -2
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@@ -13,11 +13,11 @@ jupyter:
# Tree-Based Methods
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch08-baggboost-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch08-baggboost-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch08-baggboost-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch08-baggboost-lab.ipynb)
We import some of our usual libraries at this top
Ch08-baggboost-lab.ipynb
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Ch09-svm-lab.Rmd
+2 -2
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@@ -13,11 +13,11 @@ jupyter:
# Support Vector Machines
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch09-svm-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch09-svm-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch09-svm-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch09-svm-lab.ipynb)
In this lab, we use the `sklearn.svm` library to demonstrate the support
Ch09-svm-lab.ipynb
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Ch10-deeplearning-lab.Rmd
+2 -2
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@@ -13,11 +13,11 @@ jupyter:
# Deep Learning
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch10-deeplearning-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch10-deeplearning-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch10-deeplearning-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch10-deeplearning-lab.ipynb)
In this section we demonstrate how to fit the examples discussed
Ch10-deeplearning-lab.ipynb
+320 -327
View File
@@ -7,11 +7,11 @@
"source": [
"# Deep Learning\n",
"\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch10-deeplearning-lab.ipynb\">\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch10-deeplearning-lab.ipynb\">\n",
"<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch10-deeplearning-lab.ipynb)"
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch10-deeplearning-lab.ipynb)"
]
},
{
@@ -153,7 +153,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"Seed set to 0\n"
"Global seed set to 0\n"
]
}
],
@@ -899,357 +899,357 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 0: 100%|█████████████████████████████████████████████| 6/6 [00:01<00:00, 4.42it/s, v_num=50]\n",
"Validation: | | 0/? [00:00<?, ?it/s]\u001b[A\n",
"Epoch 0: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:01<00:00, 3.61it/s, v_num=53]\n",
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"Epoch 1: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 150.03it/s, v_num=50]\u001b[A\n",
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"Epoch 0: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:01<00:00, 3.51it/s, v_num=53]\u001b[A\n",
"Epoch 1: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 107.14it/s, v_num=53]\u001b[A\n",
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"Epoch 2: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 206.02it/s, v_num=50]\u001b[A\n",
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"Epoch 1: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 72.13it/s, v_num=53]\u001b[A\n",
"Epoch 2: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 158.76it/s, v_num=53]\u001b[A\n",
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"Epoch 3: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 209.50it/s, v_num=50]\u001b[A\n",
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"Epoch 2: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 94.09it/s, v_num=53]\u001b[A\n",
"Epoch 3: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 131.92it/s, v_num=53]\u001b[A\n",
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"Epoch 4: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 209.69it/s, v_num=50]\u001b[A\n",
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"Epoch 3: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 96.53it/s, v_num=53]\u001b[A\n",
"Epoch 4: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 52.62it/s, v_num=53]\u001b[A\n",
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"Epoch 4: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 45.57it/s, v_num=53]\u001b[A\n",
"Epoch 5: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 142.63it/s, v_num=53]\u001b[A\n",
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"Epoch 6: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 202.03it/s, v_num=50]\u001b[A\n",
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"Epoch 5: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 101.13it/s, v_num=53]\u001b[A\n",
"Epoch 6: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 158.37it/s, v_num=53]\u001b[A\n",
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"Epoch 7: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 205.02it/s, v_num=50]\u001b[A\n",
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"Epoch 6: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 112.46it/s, v_num=53]\u001b[A\n",
"Epoch 7: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 151.03it/s, v_num=53]\u001b[A\n",
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"Epoch 8: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 143.06it/s, v_num=50]\u001b[A\n",
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"Epoch 7: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 107.97it/s, v_num=53]\u001b[A\n",
"Epoch 8: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 143.05it/s, v_num=53]\u001b[A\n",
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"Epoch 9: 100%|████████████████████████████████████████████| 6/6 [00:00<00:00, 195.13it/s, v_num=50]\u001b[A\n",
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"Epoch 8: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 97.93it/s, v_num=53]\u001b[A\n",
"Epoch 9: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 162.66it/s, v_num=53]\u001b[A\n",
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"Epoch 10: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 199.01it/s, v_num=50]\u001b[A\n",
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"Epoch 9: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 110.13it/s, v_num=53]\u001b[A\n",
"Epoch 10: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 166.04it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 522.11it/s]\u001b[A\n",
"Epoch 11: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 176.66it/s, v_num=50]\u001b[A\n",
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"Epoch 10: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 81.87it/s, v_num=53]\u001b[A\n",
"Epoch 11: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 131.10it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 445.37it/s]\u001b[A\n",
"Epoch 12: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 127.61it/s, v_num=50]\u001b[A\n",
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"Epoch 11: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 96.94it/s, v_num=53]\u001b[A\n",
"Epoch 12: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 115.42it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 370.65it/s]\u001b[A\n",
"Epoch 13: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 181.79it/s, v_num=50]\u001b[A\n",
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"Epoch 12: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 87.01it/s, v_num=53]\u001b[A\n",
"Epoch 13: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 146.32it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 484.18it/s]\u001b[A\n",
"Epoch 14: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 177.02it/s, v_num=50]\u001b[A\n",
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"Epoch 13: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 82.38it/s, v_num=53]\u001b[A\n",
"Epoch 14: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 131.01it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 584.82it/s]\u001b[A\n",
"Epoch 15: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 194.87it/s, v_num=50]\u001b[A\n",
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"Epoch 14: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 74.59it/s, v_num=53]\u001b[A\n",
"Epoch 15: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 92.88it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 509.16it/s]\u001b[A\n",
"Epoch 16: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 197.01it/s, v_num=50]\u001b[A\n",
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"Epoch 15: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 61.27it/s, v_num=53]\u001b[A\n",
"Epoch 16: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 105.63it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 544.55it/s]\u001b[A\n",
"Epoch 17: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 197.88it/s, v_num=50]\u001b[A\n",
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"Epoch 16: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 79.87it/s, v_num=53]\u001b[A\n",
"Epoch 17: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 156.48it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 515.99it/s]\u001b[A\n",
"Epoch 18: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 196.15it/s, v_num=50]\u001b[A\n",
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"Epoch 17: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 65.73it/s, v_num=53]\u001b[A\n",
"Epoch 18: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 101.65it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 492.54it/s]\u001b[A\n",
"Epoch 19: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 201.80it/s, v_num=50]\u001b[A\n",
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"Validation DataLoader 0: 67%|██████████████████████████████████████████████████████████████████████████████████████████▋ | 2/3 [00:00<00:00, 475.87it/s]\u001b[A\n",
"Epoch 18: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 79.99it/s, v_num=53]\u001b[A\n",
"Epoch 19: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 154.66it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 476.95it/s]\u001b[A\n",
"Epoch 20: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 203.22it/s, v_num=50]\u001b[A\n",
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"Epoch 19: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 107.80it/s, v_num=53]\u001b[A\n",
"Epoch 20: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 147.68it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 555.76it/s]\u001b[A\n",
"Epoch 21: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 199.57it/s, v_num=50]\u001b[A\n",
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"Validation DataLoader 0: 67%|██████████████████████████████████████████████████████████████████████████████████████████▋ | 2/3 [00:00<00:00, 424.27it/s]\u001b[A\n",
"Epoch 20: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 103.53it/s, v_num=53]\u001b[A\n",
"Epoch 21: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 118.82it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 503.20it/s]\u001b[A\n",
"Epoch 22: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 195.29it/s, v_num=50]\u001b[A\n",
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"Epoch 21: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 86.64it/s, v_num=53]\u001b[A\n",
"Epoch 22: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 160.67it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 456.33it/s]\u001b[A\n",
"Epoch 23: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 198.77it/s, v_num=50]\u001b[A\n",
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"Epoch 22: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 101.11it/s, v_num=53]\u001b[A\n",
"Epoch 23: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 133.15it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 489.63it/s]\u001b[A\n",
"Epoch 24: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 166.06it/s, v_num=50]\u001b[A\n",
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"Epoch 23: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 93.10it/s, v_num=53]\u001b[A\n",
"Epoch 24: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 110.61it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 545.57it/s]\u001b[A\n",
"Epoch 25: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 191.80it/s, v_num=50]\u001b[A\n",
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"Epoch 24: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 81.61it/s, v_num=53]\u001b[A\n",
"Epoch 25: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 155.90it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 471.85it/s]\u001b[A\n",
"Epoch 26: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 194.50it/s, v_num=50]\u001b[A\n",
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"Epoch 25: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 105.66it/s, v_num=53]\u001b[A\n",
"Epoch 26: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 136.21it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 501.59it/s]\u001b[A\n",
"Epoch 27: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 194.73it/s, v_num=50]\u001b[A\n",
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"Validation DataLoader 0: 67%|██████████████████████████████████████████████████████████████████████████████████████████▋ | 2/3 [00:00<00:00, 460.38it/s]\u001b[A\n",
"Epoch 26: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 98.19it/s, v_num=53]\u001b[A\n",
"Epoch 27: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 98.91it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 526.50it/s]\u001b[A\n",
"Epoch 28: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 190.80it/s, v_num=50]\u001b[A\n",
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"Epoch 27: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 73.00it/s, v_num=53]\u001b[A\n",
"Epoch 28: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 113.16it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 477.33it/s]\u001b[A\n",
"Epoch 29: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 103.09it/s, v_num=50]\u001b[A\n",
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"Epoch 28: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 84.22it/s, v_num=53]\u001b[A\n",
"Epoch 29: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 132.53it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 542.88it/s]\u001b[A\n",
"Epoch 30: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 189.78it/s, v_num=50]\u001b[A\n",
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"Epoch 29: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 82.97it/s, v_num=53]\u001b[A\n",
"Epoch 30: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 153.61it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 520.82it/s]\u001b[A\n",
"Epoch 31: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 160.01it/s, v_num=50]\u001b[A\n",
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"Validation DataLoader 0: 67%|██████████████████████████████████████████████████████████████████████████████████████████▋ | 2/3 [00:00<00:00, 501.77it/s]\u001b[A\n",
"Epoch 30: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 110.14it/s, v_num=53]\u001b[A\n",
"Epoch 31: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 144.47it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 527.52it/s]\u001b[A\n",
"Epoch 32: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 195.70it/s, v_num=50]\u001b[A\n",
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"Validation DataLoader 0: 33%|█████████████████████████████████████████████▎ | 1/3 [00:00<00:00, 604.19it/s]\u001b[A\n",
"Validation DataLoader 0: 67%|██████████████████████████████████████████████████████████████████████████████████████████▋ | 2/3 [00:00<00:00, 536.49it/s]\u001b[A\n",
"Epoch 31: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 105.80it/s, v_num=53]\u001b[A\n",
"Epoch 32: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 146.62it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 470.28it/s]\u001b[A\n",
"Epoch 33: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 190.77it/s, v_num=50]\u001b[A\n",
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"Epoch 32: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 109.10it/s, v_num=53]\u001b[A\n",
"Epoch 33: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 155.55it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 471.41it/s]\u001b[A\n",
"Epoch 34: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 188.33it/s, v_num=50]\u001b[A\n",
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"Epoch 33: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 112.52it/s, v_num=53]\u001b[A\n",
"Epoch 34: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 169.35it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 504.87it/s]\u001b[A\n",
"Epoch 35: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 186.16it/s, v_num=50]\u001b[A\n",
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"Epoch 34: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 112.99it/s, v_num=53]\u001b[A\n",
"Epoch 35: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 53.05it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 509.43it/s]\u001b[A\n",
"Epoch 36: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 189.45it/s, v_num=50]\u001b[A\n",
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"Epoch 35: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 44.52it/s, v_num=53]\u001b[A\n",
"Epoch 36: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 173.80it/s, v_num=53]\u001b[A\n",
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"Epoch 37: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 190.02it/s, v_num=50]\u001b[A\n",
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"Epoch 36: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 115.41it/s, v_num=53]\u001b[A\n",
"Epoch 37: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 157.70it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 571.74it/s]\u001b[A\n",
"Epoch 38: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 194.72it/s, v_num=50]\u001b[A\n",
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"Epoch 37: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 113.64it/s, v_num=53]\u001b[A\n",
"Epoch 38: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 107.63it/s, v_num=53]\u001b[A\n",
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"Validation DataLoader 0: 100%|██████████████████████████████████████| 3/3 [00:00<00:00, 470.60it/s]\u001b[A\n",
"Epoch 39: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 176.34it/s, v_num=50]\u001b[A\n",
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"Epoch 38: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 84.98it/s, v_num=53]\u001b[A\n",
"Epoch 39: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 167.69it/s, v_num=53]\u001b[A\n",
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"Epoch 40: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 203.51it/s, v_num=50]\u001b[A\n",
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"Epoch 39: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 114.73it/s, v_num=53]\u001b[A\n",
"Epoch 40: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 181.69it/s, v_num=53]\u001b[A\n",
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"Epoch 41: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 187.93it/s, v_num=50]\u001b[A\n",
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"Epoch 40: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 117.14it/s, v_num=53]\u001b[A\n",
"Epoch 41: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 150.01it/s, v_num=53]\u001b[A\n",
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"Epoch 42: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 165.53it/s, v_num=50]\u001b[A\n",
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"Epoch 41: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 103.76it/s, v_num=53]\u001b[A\n",
"Epoch 42: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 168.63it/s, v_num=53]\u001b[A\n",
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"Epoch 43: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 160.23it/s, v_num=50]\u001b[A\n",
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"Epoch 42: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 113.95it/s, v_num=53]\u001b[A\n",
"Epoch 43: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 167.74it/s, v_num=53]\u001b[A\n",
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"Epoch 44: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 178.87it/s, v_num=53]\u001b[A\n",
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"Epoch 45: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 127.78it/s, v_num=53]\u001b[A\n",
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"Epoch 46: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 114.40it/s, v_num=53]\u001b[A\n",
"Epoch 47: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 177.12it/s, v_num=53]\u001b[A\n",
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"Epoch 48: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 135.22it/s, v_num=53]\u001b[A\n",
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"Epoch 48: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 98.30it/s, v_num=53]\u001b[A\n",
"Epoch 49: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 184.24it/s, v_num=53]\u001b[A\n",
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"Epoch 49: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 128.81it/s, v_num=50]\u001b[A"
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"Epoch 49: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 122.31it/s, v_num=53]\u001b[A\n",
"Epoch 49: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 119.24it/s, v_num=53]\u001b[A"
]
},
{
@@ -1263,7 +1263,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch 49: 100%|███████████████████████████████████████████| 6/6 [00:00<00:00, 117.06it/s, v_num=50]\n"
"Epoch 49: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 106.77it/s, v_num=53]\n"
]
}
],
@@ -1303,19 +1303,19 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Testing DataLoader 0: 100%|█████████████████████████████████████████| 3/3 [00:00<00:00, 303.70it/s]\n",
"Testing DataLoader 0: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 241.10it/s]\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_loss 107904.640625\n",
" test_mae 221.8314971923828\n",
" test_loss 125020.234375\n",
" test_mae 250.8108367919922\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 107904.640625, 'test_mae': 221.8314971923828}]"
"[{'test_loss': 125020.234375, 'test_mae': 250.8108367919922}]"
]
},
"execution_count": 28,
@@ -1414,7 +1414,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
@@ -1462,7 +1462,7 @@
{
"data": {
"text/plain": [
"tensor(221.8315, grad_fn=<MeanBackward0>)"
"tensor(250.8108, grad_fn=<MeanBackward0>)"
]
},
"execution_count": 32,
@@ -1899,7 +1899,7 @@
"outputs": [
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
@@ -1940,17 +1940,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_accuracy 0.9620000123977661\n",
" test_loss 0.15120187401771545\n",
" test_accuracy 0.9641000032424927\n",
" test_loss 0.15847289562225342\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 0.15120187401771545, 'test_accuracy': 0.9620000123977661}]"
"[{'test_loss': 0.15847289562225342, 'test_accuracy': 0.9641000032424927}]"
]
},
"execution_count": 44,
@@ -2013,7 +2013,8 @@
"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_test2025/lib/python3.11/site-packages/pytorch_lightning/trainer/connectors/logger_connector/logger_connector.py:75: 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",
"/Users/jonathantaylor/anaconda3/envs/stats216_2024/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",
@@ -2057,17 +2058,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_accuracy 0.916100025177002\n",
" test_loss 0.3469300866127014\n",
" test_accuracy 0.9235000014305115\n",
" test_loss 0.3271547853946686\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 0.3469300866127014, 'test_accuracy': 0.916100025177002}]"
"[{'test_loss': 0.3271547853946686, 'test_accuracy': 0.9235000014305115}]"
]
},
"execution_count": 47,
@@ -2249,7 +2250,7 @@
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 1000x1000 with 25 Axes>"
]
@@ -2544,7 +2545,7 @@
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
@@ -2587,17 +2588,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_accuracy 0.4269999861717224\n",
" test_loss 2.45865797996521\n",
" test_accuracy 0.4221000075340271\n",
" test_loss 2.474802255630493\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 2.45865797996521, 'test_accuracy': 0.4269999861717224}]"
"[{'test_loss': 2.474802255630493, 'test_accuracy': 0.4221000075340271}]"
]
},
"execution_count": 60,
@@ -2656,6 +2657,8 @@
"0 Non-trainable params\n",
"964 K Total params\n",
"3.858 Total estimated model params size (MB)\n",
"/Users/jonathantaylor/anaconda3/envs/stats216_2024/lib/python3.11/site-packages/torchmetrics/functional/classification/accuracy.py:77: UserWarning: MPS: no support for int64 reduction ops, casting it to int32 (Triggered internally at /Users/runner/work/pytorch/pytorch/pytorch/aten/src/ATen/native/mps/operations/ReduceOps.mm:144.)\n",
" tp = tp.sum(dim=0 if multidim_average == \"global\" else 1)\n",
"`Trainer.fit` stopped: `max_epochs=30` reached.\n"
]
}
@@ -3259,34 +3262,34 @@
"text": [
"Image: book_images/Cape_Weaver.jpg\n",
" label prob\n",
"0 jacamar 0.297499\n",
"1 macaw 0.068107\n",
"2 lorikeet 0.051105\n",
"0 jacamar 0.298104\n",
"1 macaw 0.068012\n",
"2 lorikeet 0.051065\n",
"Image: book_images/Flamingo.jpg\n",
" label prob\n",
"0 flamingo 0.609515\n",
"1 spoonbill 0.013586\n",
"2 American_egret 0.002132\n",
"0 flamingo 0.606624\n",
"1 spoonbill 0.013324\n",
"2 American_egret 0.002130\n",
"Image: book_images/Hawk_Fountain.jpg\n",
" label prob\n",
"0 kite 0.184682\n",
"1 robin 0.084021\n",
"2 great_grey_owl 0.061274\n",
"0 kite 0.187797\n",
"1 robin 0.084580\n",
"2 great_grey_owl 0.059789\n",
"Image: book_images/Hawk_cropped.jpg\n",
" label prob\n",
"0 kite 0.453833\n",
"1 great_grey_owl 0.015914\n",
"2 jay 0.012210\n",
"0 kite 0.454471\n",
"1 great_grey_owl 0.015789\n",
"2 jay 0.011916\n",
"Image: book_images/Lhasa_Apso.jpg\n",
" label prob\n",
"0 Lhasa 0.260317\n",
"1 Shih-Tzu 0.097196\n",
"2 Tibetan_terrier 0.032820\n",
"0 Lhasa 0.260186\n",
"1 Shih-Tzu 0.097995\n",
"2 Tibetan_terrier 0.032107\n",
"Image: book_images/Sleeping_Cat.jpg\n",
" label prob\n",
"0 Persian_cat 0.163070\n",
"1 tabby 0.074143\n",
"2 tiger_cat 0.042578\n"
"0 Persian_cat 0.163612\n",
"1 tabby 0.074585\n",
"2 tiger_cat 0.042531\n"
]
}
],
@@ -3607,7 +3610,8 @@
"0 Non-trainable params\n",
"160 K Total params\n",
"0.641 Total estimated model params size (MB)\n",
"/Users/jonathantaylor/anaconda3/envs/ISLP_test2025/lib/python3.11/site-packages/pytorch_lightning/loops/fit_loop.py:298: 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/stats216_2024/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",
"`Trainer.fit` stopped: `max_epochs=30` reached.\n"
]
}
@@ -3644,17 +3648,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_accuracy 0.8450000286102295\n",
" test_loss 1.2167928218841553\n",
" test_accuracy 0.8492000102996826\n",
" test_loss 1.2837774753570557\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 1.2167928218841553, 'test_accuracy': 0.8450000286102295}]"
"[{'test_loss': 1.2837774753570557, 'test_accuracy': 0.8492000102996826}]"
]
},
"execution_count": 77,
@@ -3853,7 +3857,7 @@
"outputs": [
{
"data": {
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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1600x800 with 2 Axes>"
]
@@ -4133,17 +4137,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_accuracy 0.8462799787521362\n",
" test_loss 0.7731857895851135\n",
" test_accuracy 0.8532000184059143\n",
" test_loss 0.8377798199653625\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 0.7731857895851135, 'test_accuracy': 0.8462799787521362}]"
"[{'test_loss': 0.8377798199653625, 'test_accuracy': 0.8532000184059143}]"
]
},
"execution_count": 91,
@@ -4183,7 +4187,7 @@
},
{
"data": {
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truncated
"text/plain": [
"<Figure size 600x600 with 1 Axes>"
]
@@ -4549,18 +4553,7 @@
"execution_count": 103,
"id": "72ab9a66",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70820/3890359531.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
" Y_t = torch.tensor(Y[mask].astype(np.float32))\n",
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70820/3890359531.py:4: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n",
" Y_t = torch.tensor(Y[mask].astype(np.float32))\n"
]
}
],
"outputs": [],
"source": [
"datasets = []\n",
"for mask in [train, ~train]:\n",
@@ -4746,17 +4739,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_loss 0.616382360458374\n",
" test_r2 0.4150230884552002\n",
" test_loss 0.6186699867248535\n",
" test_r2 0.4128519892692566\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 0.616382360458374, 'test_r2': 0.4150230884552002}]"
"[{'test_loss': 0.6186699867248535, 'test_r2': 0.4128519892692566}]"
]
},
"execution_count": 108,
@@ -4914,17 +4907,17 @@
"output_type": "stream",
"text": [
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" Test metric DataLoader 0\n",
"Runningstage.testing metric DataLoader 0\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
" test_loss 0.5626183152198792\n",
" test_r2 0.4660477638244629\n",
" test_loss 0.564926266670227\n",
" test_r2 0.46385735273361206\n",
"────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n"
]
},
{
"data": {
"text/plain": [
"[{'test_loss': 0.5626183152198792, 'test_r2': 0.4660477638244629}]"
"[{'test_loss': 0.564926266670227, 'test_r2': 0.46385735273361206}]"
]
},
"execution_count": 113,
Ch11-surv-lab.Rmd
+2 -2
View File
@@ -13,11 +13,11 @@ jupyter:
# Survival Analysis
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch11-surv-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch11-surv-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch11-surv-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch11-surv-lab.ipynb)
In this lab, we perform survival analyses on three separate data
Ch11-surv-lab.ipynb
+152 -179
View File
@@ -7,11 +7,11 @@
"source": [
"# Survival Analysis\n",
"\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch11-surv-lab.ipynb\">\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch11-surv-lab.ipynb\">\n",
"<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch11-surv-lab.ipynb)"
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch11-surv-lab.ipynb)"
]
},
{
@@ -37,10 +37,10 @@
"id": "80c238e6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:12.018813Z",
"iopub.status.busy": "2025-04-03T19:34:12.018724Z",
"iopub.status.idle": "2025-04-03T19:34:12.943735Z",
"shell.execute_reply": "2025-04-03T19:34:12.943404Z"
"iopub.execute_input": "2026-02-02T23:40:28.233456Z",
"iopub.status.busy": "2026-02-02T23:40:28.233170Z",
"iopub.status.idle": "2026-02-02T23:40:29.349388Z",
"shell.execute_reply": "2026-02-02T23:40:29.349073Z"
}
},
"outputs": [],
@@ -67,10 +67,10 @@
"id": "a236fb17",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:12.945440Z",
"iopub.status.busy": "2025-04-03T19:34:12.945303Z",
"iopub.status.idle": "2025-04-03T19:34:13.005265Z",
"shell.execute_reply": "2025-04-03T19:34:13.005006Z"
"iopub.execute_input": "2026-02-02T23:40:29.351117Z",
"iopub.status.busy": "2026-02-02T23:40:29.350968Z",
"iopub.status.idle": "2026-02-02T23:40:29.458922Z",
"shell.execute_reply": "2026-02-02T23:40:29.458662Z"
}
},
"outputs": [],
@@ -100,10 +100,10 @@
"id": "4dd4ddba",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.006753Z",
"iopub.status.busy": "2025-04-03T19:34:13.006648Z",
"iopub.status.idle": "2025-04-03T19:34:13.012550Z",
"shell.execute_reply": "2025-04-03T19:34:13.012293Z"
"iopub.execute_input": "2026-02-02T23:40:29.460452Z",
"iopub.status.busy": "2026-02-02T23:40:29.460361Z",
"iopub.status.idle": "2026-02-02T23:40:29.466324Z",
"shell.execute_reply": "2026-02-02T23:40:29.466096Z"
}
},
"outputs": [
@@ -138,10 +138,10 @@
"id": "ae9435b1",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.013818Z",
"iopub.status.busy": "2025-04-03T19:34:13.013731Z",
"iopub.status.idle": "2025-04-03T19:34:13.016497Z",
"shell.execute_reply": "2025-04-03T19:34:13.016291Z"
"iopub.execute_input": "2026-02-02T23:40:29.467504Z",
"iopub.status.busy": "2026-02-02T23:40:29.467412Z",
"iopub.status.idle": "2026-02-02T23:40:29.470004Z",
"shell.execute_reply": "2026-02-02T23:40:29.469792Z"
},
"lines_to_next_cell": 2
},
@@ -149,10 +149,9 @@
{
"data": {
"text/plain": [
"sex\n",
"Female 45\n",
"Male 43\n",
"Name: count, dtype: int64"
"Name: sex, dtype: int64"
]
},
"execution_count": 4,
@@ -170,10 +169,10 @@
"id": "a6e94032",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.017537Z",
"iopub.status.busy": "2025-04-03T19:34:13.017456Z",
"iopub.status.idle": "2025-04-03T19:34:13.019991Z",
"shell.execute_reply": "2025-04-03T19:34:13.019789Z"
"iopub.execute_input": "2026-02-02T23:40:29.471059Z",
"iopub.status.busy": "2026-02-02T23:40:29.470973Z",
"iopub.status.idle": "2026-02-02T23:40:29.473403Z",
"shell.execute_reply": "2026-02-02T23:40:29.473149Z"
},
"lines_to_next_cell": 2
},
@@ -181,12 +180,11 @@
{
"data": {
"text/plain": [
"diagnosis\n",
"Meningioma 42\n",
"HG glioma 22\n",
"Other 14\n",
"LG glioma 9\n",
"Name: count, dtype: int64"
"Name: diagnosis, dtype: int64"
]
},
"execution_count": 5,
@@ -204,10 +202,10 @@
"id": "afa05da1",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.021104Z",
"iopub.status.busy": "2025-04-03T19:34:13.021020Z",
"iopub.status.idle": "2025-04-03T19:34:13.023271Z",
"shell.execute_reply": "2025-04-03T19:34:13.023062Z"
"iopub.execute_input": "2026-02-02T23:40:29.474413Z",
"iopub.status.busy": "2026-02-02T23:40:29.474348Z",
"iopub.status.idle": "2026-02-02T23:40:29.477359Z",
"shell.execute_reply": "2026-02-02T23:40:29.477157Z"
},
"lines_to_next_cell": 2
},
@@ -215,10 +213,9 @@
{
"data": {
"text/plain": [
"status\n",
"0 53\n",
"1 35\n",
"Name: count, dtype: int64"
"Name: status, dtype: int64"
]
},
"execution_count": 6,
@@ -261,10 +258,10 @@
"id": "34c7c534",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.024340Z",
"iopub.status.busy": "2025-04-03T19:34:13.024274Z",
"iopub.status.idle": "2025-04-03T19:34:13.214355Z",
"shell.execute_reply": "2025-04-03T19:34:13.211396Z"
"iopub.execute_input": "2026-02-02T23:40:29.478404Z",
"iopub.status.busy": "2026-02-02T23:40:29.478324Z",
"iopub.status.idle": "2026-02-02T23:40:29.594965Z",
"shell.execute_reply": "2026-02-02T23:40:29.592314Z"
}
},
"outputs": [
@@ -280,7 +277,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -327,24 +324,16 @@
"id": "5e742ebe",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.217705Z",
"iopub.status.busy": "2025-04-03T19:34:13.217547Z",
"iopub.status.idle": "2025-04-03T19:34:13.319409Z",
"shell.execute_reply": "2025-04-03T19:34:13.319126Z"
"iopub.execute_input": "2026-02-02T23:40:29.605351Z",
"iopub.status.busy": "2026-02-02T23:40:29.604913Z",
"iopub.status.idle": "2026-02-02T23:40:29.756933Z",
"shell.execute_reply": "2026-02-02T23:40:29.751150Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70612/380004221.py:3: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
" for sex, df in BrainCancer.groupby('sex'):\n"
]
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -380,10 +369,10 @@
"id": "4106e397",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.320825Z",
"iopub.status.busy": "2025-04-03T19:34:13.320720Z",
"iopub.status.idle": "2025-04-03T19:34:13.369010Z",
"shell.execute_reply": "2025-04-03T19:34:13.368744Z"
"iopub.execute_input": "2026-02-02T23:40:29.769387Z",
"iopub.status.busy": "2026-02-02T23:40:29.769225Z",
"iopub.status.idle": "2026-02-02T23:40:29.818623Z",
"shell.execute_reply": "2026-02-02T23:40:29.818386Z"
},
"lines_to_next_cell": 2
},
@@ -493,10 +482,10 @@
"id": "8962942d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.370379Z",
"iopub.status.busy": "2025-04-03T19:34:13.370240Z",
"iopub.status.idle": "2025-04-03T19:34:13.390186Z",
"shell.execute_reply": "2025-04-03T19:34:13.389904Z"
"iopub.execute_input": "2026-02-02T23:40:29.819898Z",
"iopub.status.busy": "2026-02-02T23:40:29.819778Z",
"iopub.status.idle": "2026-02-02T23:40:29.842571Z",
"shell.execute_reply": "2026-02-02T23:40:29.842339Z"
}
},
"outputs": [
@@ -586,10 +575,10 @@
"id": "d923fe3d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.391470Z",
"iopub.status.busy": "2025-04-03T19:34:13.391389Z",
"iopub.status.idle": "2025-04-03T19:34:13.395931Z",
"shell.execute_reply": "2025-04-03T19:34:13.395714Z"
"iopub.execute_input": "2026-02-02T23:40:29.844036Z",
"iopub.status.busy": "2026-02-02T23:40:29.843960Z",
"iopub.status.idle": "2026-02-02T23:40:29.848436Z",
"shell.execute_reply": "2026-02-02T23:40:29.848213Z"
}
},
"outputs": [
@@ -692,10 +681,10 @@
"id": "43b23849",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.397443Z",
"iopub.status.busy": "2025-04-03T19:34:13.397345Z",
"iopub.status.idle": "2025-04-03T19:34:13.425936Z",
"shell.execute_reply": "2025-04-03T19:34:13.425693Z"
"iopub.execute_input": "2026-02-02T23:40:29.849715Z",
"iopub.status.busy": "2026-02-02T23:40:29.849642Z",
"iopub.status.idle": "2026-02-02T23:40:29.878002Z",
"shell.execute_reply": "2026-02-02T23:40:29.877763Z"
}
},
"outputs": [
@@ -840,10 +829,10 @@
"id": "20f95f4d",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.427427Z",
"iopub.status.busy": "2025-04-03T19:34:13.427328Z",
"iopub.status.idle": "2025-04-03T19:34:13.430341Z",
"shell.execute_reply": "2025-04-03T19:34:13.430045Z"
"iopub.execute_input": "2026-02-02T23:40:29.879409Z",
"iopub.status.busy": "2026-02-02T23:40:29.879331Z",
"iopub.status.idle": "2026-02-02T23:40:29.882681Z",
"shell.execute_reply": "2026-02-02T23:40:29.882457Z"
}
},
"outputs": [],
@@ -873,10 +862,10 @@
"id": "18ef52a9",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.431840Z",
"iopub.status.busy": "2025-04-03T19:34:13.431760Z",
"iopub.status.idle": "2025-04-03T19:34:13.436751Z",
"shell.execute_reply": "2025-04-03T19:34:13.436503Z"
"iopub.execute_input": "2026-02-02T23:40:29.883885Z",
"iopub.status.busy": "2026-02-02T23:40:29.883777Z",
"iopub.status.idle": "2026-02-02T23:40:29.888549Z",
"shell.execute_reply": "2026-02-02T23:40:29.888317Z"
}
},
"outputs": [
@@ -1001,10 +990,10 @@
"id": "dc826bbc",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.438051Z",
"iopub.status.busy": "2025-04-03T19:34:13.437925Z",
"iopub.status.idle": "2025-04-03T19:34:13.445359Z",
"shell.execute_reply": "2025-04-03T19:34:13.445106Z"
"iopub.execute_input": "2026-02-02T23:40:29.896273Z",
"iopub.status.busy": "2026-02-02T23:40:29.896164Z",
"iopub.status.idle": "2026-02-02T23:40:29.904155Z",
"shell.execute_reply": "2026-02-02T23:40:29.903918Z"
}
},
"outputs": [
@@ -1143,10 +1132,10 @@
"id": "867045f7",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.446788Z",
"iopub.status.busy": "2025-04-03T19:34:13.446666Z",
"iopub.status.idle": "2025-04-03T19:34:13.451983Z",
"shell.execute_reply": "2025-04-03T19:34:13.451782Z"
"iopub.execute_input": "2026-02-02T23:40:29.905454Z",
"iopub.status.busy": "2026-02-02T23:40:29.905357Z",
"iopub.status.idle": "2026-02-02T23:40:29.911172Z",
"shell.execute_reply": "2026-02-02T23:40:29.910926Z"
},
"lines_to_next_cell": 0
},
@@ -1304,17 +1293,17 @@
"id": "9fa60bac",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.453343Z",
"iopub.status.busy": "2025-04-03T19:34:13.453269Z",
"iopub.status.idle": "2025-04-03T19:34:13.508384Z",
"shell.execute_reply": "2025-04-03T19:34:13.508148Z"
"iopub.execute_input": "2026-02-02T23:40:29.912461Z",
"iopub.status.busy": "2026-02-02T23:40:29.912377Z",
"iopub.status.idle": "2026-02-02T23:40:29.992285Z",
"shell.execute_reply": "2026-02-02T23:40:29.992056Z"
},
"lines_to_next_cell": 2
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1347,16 +1336,16 @@
"id": "f8c1a98e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.509713Z",
"iopub.status.busy": "2025-04-03T19:34:13.509616Z",
"iopub.status.idle": "2025-04-03T19:34:13.575866Z",
"shell.execute_reply": "2025-04-03T19:34:13.575533Z"
"iopub.execute_input": "2026-02-02T23:40:29.993691Z",
"iopub.status.busy": "2026-02-02T23:40:29.993598Z",
"iopub.status.idle": "2026-02-02T23:40:30.079014Z",
"shell.execute_reply": "2026-02-02T23:40:30.078774Z"
}
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1392,10 +1381,10 @@
"id": "cd1ed9ac",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.577381Z",
"iopub.status.busy": "2025-04-03T19:34:13.577276Z",
"iopub.status.idle": "2025-04-03T19:34:13.603522Z",
"shell.execute_reply": "2025-04-03T19:34:13.603251Z"
"iopub.execute_input": "2026-02-02T23:40:30.080486Z",
"iopub.status.busy": "2026-02-02T23:40:30.080397Z",
"iopub.status.idle": "2026-02-02T23:40:30.111760Z",
"shell.execute_reply": "2026-02-02T23:40:30.111406Z"
},
"lines_to_next_cell": 2
},
@@ -1481,10 +1470,10 @@
"id": "d53335b0",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.604965Z",
"iopub.status.busy": "2025-04-03T19:34:13.604889Z",
"iopub.status.idle": "2025-04-03T19:34:13.639892Z",
"shell.execute_reply": "2025-04-03T19:34:13.639595Z"
"iopub.execute_input": "2026-02-02T23:40:30.113137Z",
"iopub.status.busy": "2026-02-02T23:40:30.113022Z",
"iopub.status.idle": "2026-02-02T23:40:30.146933Z",
"shell.execute_reply": "2026-02-02T23:40:30.146681Z"
}
},
"outputs": [
@@ -1625,10 +1614,10 @@
"id": "582c992b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.641344Z",
"iopub.status.busy": "2025-04-03T19:34:13.641249Z",
"iopub.status.idle": "2025-04-03T19:34:13.644691Z",
"shell.execute_reply": "2025-04-03T19:34:13.644397Z"
"iopub.execute_input": "2026-02-02T23:40:30.148205Z",
"iopub.status.busy": "2026-02-02T23:40:30.148127Z",
"iopub.status.idle": "2026-02-02T23:40:30.151319Z",
"shell.execute_reply": "2026-02-02T23:40:30.151090Z"
}
},
"outputs": [],
@@ -1663,10 +1652,10 @@
"id": "f3367dad",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.646236Z",
"iopub.status.busy": "2025-04-03T19:34:13.646138Z",
"iopub.status.idle": "2025-04-03T19:34:13.653905Z",
"shell.execute_reply": "2025-04-03T19:34:13.653638Z"
"iopub.execute_input": "2026-02-02T23:40:30.152366Z",
"iopub.status.busy": "2026-02-02T23:40:30.152298Z",
"iopub.status.idle": "2026-02-02T23:40:30.159456Z",
"shell.execute_reply": "2026-02-02T23:40:30.159240Z"
}
},
"outputs": [],
@@ -1695,10 +1684,10 @@
"id": "fdfd2789",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.655350Z",
"iopub.status.busy": "2025-04-03T19:34:13.655251Z",
"iopub.status.idle": "2025-04-03T19:34:13.659296Z",
"shell.execute_reply": "2025-04-03T19:34:13.659041Z"
"iopub.execute_input": "2026-02-02T23:40:30.160732Z",
"iopub.status.busy": "2026-02-02T23:40:30.160661Z",
"iopub.status.idle": "2026-02-02T23:40:30.164225Z",
"shell.execute_reply": "2026-02-02T23:40:30.163999Z"
}
},
"outputs": [
@@ -1807,10 +1796,10 @@
"id": "1a9b68c8",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.660480Z",
"iopub.status.busy": "2025-04-03T19:34:13.660411Z",
"iopub.status.idle": "2025-04-03T19:34:13.701074Z",
"shell.execute_reply": "2025-04-03T19:34:13.693437Z"
"iopub.execute_input": "2026-02-02T23:40:30.165320Z",
"iopub.status.busy": "2026-02-02T23:40:30.165249Z",
"iopub.status.idle": "2026-02-02T23:40:30.181030Z",
"shell.execute_reply": "2026-02-02T23:40:30.179683Z"
}
},
"outputs": [],
@@ -1854,10 +1843,10 @@
"id": "d2118fdd",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.732130Z",
"iopub.status.busy": "2025-04-03T19:34:13.731547Z",
"iopub.status.idle": "2025-04-03T19:34:13.737683Z",
"shell.execute_reply": "2025-04-03T19:34:13.734951Z"
"iopub.execute_input": "2026-02-02T23:40:30.185644Z",
"iopub.status.busy": "2026-02-02T23:40:30.185283Z",
"iopub.status.idle": "2026-02-02T23:40:30.249849Z",
"shell.execute_reply": "2026-02-02T23:40:30.249050Z"
},
"lines_to_next_cell": 0
},
@@ -1885,10 +1874,10 @@
"id": "68304ba6",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.746538Z",
"iopub.status.busy": "2025-04-03T19:34:13.745498Z",
"iopub.status.idle": "2025-04-03T19:34:13.870126Z",
"shell.execute_reply": "2025-04-03T19:34:13.866238Z"
"iopub.execute_input": "2026-02-02T23:40:30.262130Z",
"iopub.status.busy": "2026-02-02T23:40:30.261849Z",
"iopub.status.idle": "2026-02-02T23:40:30.398029Z",
"shell.execute_reply": "2026-02-02T23:40:30.396818Z"
}
},
"outputs": [],
@@ -1914,10 +1903,10 @@
"id": "becf4cd2",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.875564Z",
"iopub.status.busy": "2025-04-03T19:34:13.875279Z",
"iopub.status.idle": "2025-04-03T19:34:13.886526Z",
"shell.execute_reply": "2025-04-03T19:34:13.884362Z"
"iopub.execute_input": "2026-02-02T23:40:30.410349Z",
"iopub.status.busy": "2026-02-02T23:40:30.403028Z",
"iopub.status.idle": "2026-02-02T23:40:30.435600Z",
"shell.execute_reply": "2026-02-02T23:40:30.435349Z"
},
"lines_to_next_cell": 2
},
@@ -2022,10 +2011,10 @@
"id": "e480331c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.891617Z",
"iopub.status.busy": "2025-04-03T19:34:13.891299Z",
"iopub.status.idle": "2025-04-03T19:34:13.898541Z",
"shell.execute_reply": "2025-04-03T19:34:13.896872Z"
"iopub.execute_input": "2026-02-02T23:40:30.436950Z",
"iopub.status.busy": "2026-02-02T23:40:30.436873Z",
"iopub.status.idle": "2026-02-02T23:40:30.438955Z",
"shell.execute_reply": "2026-02-02T23:40:30.438757Z"
}
},
"outputs": [
@@ -2058,21 +2047,13 @@
"id": "a194c96e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.901959Z",
"iopub.status.busy": "2025-04-03T19:34:13.901236Z",
"iopub.status.idle": "2025-04-03T19:34:13.997840Z",
"shell.execute_reply": "2025-04-03T19:34:13.997575Z"
"iopub.execute_input": "2026-02-02T23:40:30.439995Z",
"iopub.status.busy": "2026-02-02T23:40:30.439929Z",
"iopub.status.idle": "2026-02-02T23:40:30.560685Z",
"shell.execute_reply": "2026-02-02T23:40:30.560280Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70612/1365832640.py:3: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
" for center, df in D.groupby('Center'):\n"
]
},
{
"data": {
"text/plain": [
@@ -2085,7 +2066,7 @@
},
{
"data": {
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truncated
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAp8AAAK9CAYAAABijAc1AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8g+/7EAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdd5gdZdn48e/MnDm9bK/Z7KZsGgkJCQZCCQktBqQpYkCqAv7oAVTkVQRRQBEVXomIUkSK4AsSFCLFJCAtBAgE0uumbLbX0+v8/pjNOTk5u+k99+e6zrVTnpl5Zgvcecr9KIZhGAghhBBCCLEPqPu7AkIIIYQQ4vAhwacQQgghhNhnJPgUQgghhBD7jASfQgghhBBin5HgUwghhBBC7DMSfAohhBBCiH1Ggk8hhBBCCLHPSPAphBBCCCH2GQk+hRBCCCHEPiPBpxCHIEVRuP766/fY/f7yl7+gKAqffPLJdstOmjSJSZMmpffr6upQFIW//OUv6WN33XUXiqLssfrtCU1NTZx//vkUFhaiKAoPPvjgXn2eoijcdddd6f3N3+O6urr0sa2/l/vS22+/jaIovP322/vl+Qe7mpoaLr/88u2W6+3nLsShToJPIfaRzf+T2fyx2+0MGTKE66+/nqampv1dvf3u3nvvZebMmfvt+TfffDNvvPEGt99+O08//TRf/epX+ywbCAS48847GTlyJC6Xi8LCQsaMGcNNN93Epk2b0uVmzZqVFWDuLTU1NTm/W7W1tfzgBz+gvb19rz//YLX5H0Gtra29nq+pqeFrX/vaPq6VEIc+y/6ugBCHm7vvvpsBAwYQiUR47733eOSRR5g1axaLFi3C6XTu7+rttjfffHO7ZX7yk5/wox/9KOvYvffey/nnn8+55567l2q2bXPmzOGcc87h+9///jbLxeNxJk6cyLJly7jsssu44YYbCAQCLF68mOeee47zzjuPiooKwAw+Z8yY0WsAGg6HsVj23H+Cx4wZw6233gpAJBLh008/5cEHH+Sdd95h/vz5O32/iRMnEg6HsVqte6yOQggBEnwKsc9NnTqVo48+GoArr7ySwsJCfvvb3/LKK69w4YUX9npNMBjE5XLty2rush0JViwWyx4NvPaE5uZm8vLytltu5syZfPbZZzz77LNcdNFFWecikQixWGyHnme323elmn2qrKzk4osvTu9feeWVuN1uHnjgAVauXEltbe1O3U9V1T1eRyGEAOl2F2K/O/nkkwFYu3YtAJdffjlut5vVq1dzxhln4PF4+Pa3vw2YQeitt95KVVUVNpuNoUOH8sADD2AYRq/3fvbZZxk6dCh2u51x48bx3//+N+v8unXruPbaaxk6dCgOh4PCwkK++c1v9jn+LBQK8b3vfY/CwkK8Xi+XXnopHR0dWWV2ZJzi1mM+FUUhGAzy1FNPpbuOL7/8cubOnYuiKLz88ss593juuedQFIUPP/xwm89as2YN3/zmNykoKMDpdHLsscfy2muvpc9vHg5hGAYzZsxIP78vq1evBuD444/POWe32/F6vYD5c5wxY0b6/ba+79ZjPveGsrIygJxAf9myZZx//vkUFBRgt9s5+uij+ec//5lVprcxn5MmTWLkyJEsWbKEyZMn43Q6qays5P7778959rp16zj77LNxuVyUlJSkhzXs6DjSzz77jKlTp+L1enG73ZxyyinMmzcvq8zmn93777/PLbfcQnFxMS6Xi/POO4+WlpYd/C7tnJ39G9zS4sWLOfnkk3E4HPTr149f/OIXpFKpvVJPIQ5kB1bTgxCHoc3BTGFhYfpYIpFgypQpnHDCCTzwwAM4nU4Mw+Dss89m7ty5fPe732XMmDG88cYb/OAHP6C+vp7f/e53Wfd95513eOGFF7jxxhux2Wz84Q9/4Ktf/Srz589n5MiRAHz88cd88MEHTJs2jX79+lFXV8cjjzzCpEmTWLJkSc4wgOuvv568vDzuuusuli9fziOPPMK6devSgcquevrpp7nyyisZP348V199NQCDBg3i2GOPpaqqimeffZbzzjsv65pnn32WQYMGMWHChD7v29TUxHHHHUcoFOLGG2+ksLCQp556irPPPpsXX3yR8847j4kTJ/L0009zySWXcNppp3HppZdus67V1dUA/PWvf+UnP/lJn+/9ve99j02bNvHWW2/x9NNP78y3Y5fE4/H02MVIJMJnn33Gb3/7WyZOnMiAAQPS5RYvXszxxx9PZWUlP/rRj3C5XPz973/n3HPP5aWXXsr5Pm+to6ODr371q3z961/nggsu4MUXX+S2225j1KhRTJ06FTADtJNPPpmGhgZuuukmysrKeO6555g7d+4OvcvixYs58cQT8Xq9/PCHP0TXdR599FEmTZrEO++8wzHHHJNV/oYbbiA/P58777yTuro6HnzwQa6//npeeOGFHXpeX+Nitw4Md/ZvcEuNjY1MnjyZRCKR/r7/6U9/wuFw7FAdhTikGEKIfeLJJ580AOM///mP0dLSYmzYsMF4/vnnjcLCQsPhcBgbN240DMMwLrvsMgMwfvSjH2VdP3PmTAMwfvGLX2QdP//88w1FUYxVq1aljwEGYHzyySfpY+vWrTPsdrtx3nnnpY+FQqGcen744YcGYPz1r3/Nqfu4ceOMWCyWPn7//fcbgPHKK6+kj5100knGSSedlN5fu3atARhPPvlk+tidd95pbP2fH5fLZVx22WU59bn99tsNm81mdHZ2po81NzcbFovFuPPOO3PKb2n69OkGYLz77rvpY36/3xgwYIBRU1NjJJPJ9HHAuO6667Z5P8Mwv2dDhw41AKO6utq4/PLLjccff9xoamrKKXvdddflvOeWz9uy/pu/x2vXrk0f2/p72Zfq6ur0z3zLz/HHH2+0trZmlT3llFOMUaNGGZFIJH0slUoZxx13nFFbW5s+NnfuXAMw5s6dm1WfrX83otGoUVZWZnzjG99IH/vNb35jAMbMmTPTx8LhsDFs2LCce/bm3HPPNaxWq7F69er0sU2bNhkej8eYOHFi+tjm79mpp55qpFKp9PGbb77Z0DQt63emN5t/D7f1OfPMM9Pld+ZvsLq6Ouv3efPv4kcffZQ+1tzcbPh8vpyfuxCHOul2F2IfO/XUUykuLqaqqopp06bhdrt5+eWXqayszCp3zTXXZO3PmjULTdO48cYbs47feuutGIbBv//976zjEyZMYNy4cen9/v37c8455/DGG2+QTCYBslpd4vE4bW1tDB48mLy8PBYsWJBT96uvvhpd17PqaLFYmDVr1k5+F3bcpZdeSjQa5cUXX0wfe+GFF0gkElljHHsza9Ysxo8fzwknnJA+5na7ufrqq6mrq2PJkiU7XR+Hw8FHH33ED37wA8Ds+v3ud79LeXk5N9xwA9FodKfvuSccc8wxvPXWW7z11lu8+uqr3HPPPSxevJizzz6bcDgMmC18c+bM4YILLsDv99Pa2kprayttbW1MmTKFlStXUl9fv83nuN3urO+71Wpl/PjxrFmzJn3s9ddfp7KykrPPPjt9zG63c9VVV233PZLJJG+++SbnnnsuAwcOTB8vLy/noosu4r333qO7uzvrmquvvjqrBfrEE08kmUyybt267T4P4KWXXkp/77b8lJaWZpXb2b/Bra899thjGT9+fPpYcXFxekiNEIcT6XYXYh+bMWMGQ4YMwWKxUFpaytChQ1HV7H8HWiwW+vXrl3Vs3bp1VFRU4PF4so4PHz48fX5LvU0wGTJkCKFQiJaWFsrKygiHw9x33308+eST1NfXZ41b6+rqyrl+63u63W7Ky8v3ao7CYcOG8ZWvfIVnn32W7373u4DZ5X7ssccyePDgbV67bt26nC5ayP6ebR6CsDN8Ph/3338/999/P+vWrWP27Nk88MADPPzww/h8Pn7xi1/s9D13V1FREaeeemp6/8wzz2To0KGcf/75PPbYY9xwww2sWrUKwzC44447uOOOO3q9T3Nzc84/hLbUr1+/nKEG+fn5fPHFF+n9devWMWjQoJxy2/t5AbS0tBAKhRg6dGjOueHDh5NKpdiwYQNHHHFE+nj//v1z6gPkjEfuy8SJEykqKso5vvWEq539G9z62t5+F3t7TyEOdRJ8CrGPjR8/Pj3bvS82my0nIN0bbrjhBp588kmmT5/OhAkT8Pl8KIrCtGnTDqiJEJdeeik33XQTGzduJBqNMm/ePB5++OH9XS3AHAP6ne98h/POO4+BAwfy7LPP7pfgszennHIKAP/973+54YYb0j/T73//+0yZMqXXa7YXIGqa1utxYwcm3OwtB2KdhBB9k+BTiINEdXU1//nPf/D7/VktL8uWLUuf39LKlStz7rFixQqcTifFxcUAvPjii1x22WX85je/SZeJRCJ0dnb2WoeVK1cyefLk9H4gEKChoYEzzjhjl99rs21NWJo2bRq33HILf/vb3wiHw+i6zre+9a3t3rO6uprly5fnHO/re7Y78vPzGTRoEIsWLUof29+rOCUSCcD8OQHpbmxd17NaSfe06upqlixZgmEYWd+DVatWbffa4uJinE5nnz83VVWpqqrao/XdUTv7N7j1tb39Tfb2nkIc6mTMpxAHiTPOOINkMpnT4ve73/0ORVHSM403+/DDD7PGbW7YsIFXXnmF008/Pd1SpGlaTuvQ73//+/SY0K396U9/Ih6Pp/cfeeQREolEzrN3hcvl6jPoLSoqYurUqTzzzDM8++yzfPWrX+21m3RrZ5xxBvPnz89KxxQMBvnTn/5ETU0NI0aM2Ol6Lly4sNcVcdatW8eSJUuyulE352bt6732tn/9618AjB49GoCSkhImTZrEo48+SkNDQ075PZWeaMqUKdTX12elb4pEIvz5z3/e7rWapnH66afzyiuvZA3naGpq4rnnnuOEE05Ip7Pa13b2b3Dra+fNm5eV8L+lpYVnn312r9VXiAOVtHwKcZA466yzmDx5Mj/+8Y+pq6tj9OjLine truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2118,21 +2099,13 @@
"id": "3c9eae8a",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:34:13.999260Z",
"iopub.status.busy": "2025-04-03T19:34:13.999157Z",
"iopub.status.idle": "2025-04-03T19:34:14.134838Z",
"shell.execute_reply": "2025-04-03T19:34:14.134512Z"
"iopub.execute_input": "2026-02-02T23:40:30.562105Z",
"iopub.status.busy": "2026-02-02T23:40:30.561994Z",
"iopub.status.idle": "2026-02-02T23:40:30.721091Z",
"shell.execute_reply": "2026-02-02T23:40:30.720845Z"
}
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/var/folders/16/8y65_zv174qgdp4ktlmpv12h0000gq/T/ipykernel_70612/957073325.py:3: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
" for time, df in D.groupby('Time'):\n"
]
},
{
"data": {
"text/plain": [
@@ -2145,7 +2118,7 @@
},
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -2182,10 +2155,10 @@
"id": "bb8a37eb",
"metadata": {
"execution": {
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@@ -2289,10 +2262,10 @@
"id": "e3299d19",
"metadata": {
"execution": {
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},
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},
@@ -2399,10 +2372,10 @@
"id": "b9004e25",
"metadata": {
"execution": {
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@@ -2504,10 +2477,10 @@
"id": "1780384e",
"metadata": {
"execution": {
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@@ -2612,10 +2585,10 @@
"id": "19f93f96",
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"execution": {
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@@ -2746,7 +2719,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
"version": "3.11.4"
}
},
"nbformat": 4,
Ch12-unsup-lab.Rmd
+2 -2
View File
@@ -13,11 +13,11 @@ jupyter:
# Unsupervised Learning
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch12-unsup-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch12-unsup-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch12-unsup-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch12-unsup-lab.ipynb)
In this lab we demonstrate PCA and clustering on several datasets.
Ch12-unsup-lab.ipynb
+262 -1474
View File
File diff suppressed because it is too large. Load diff
Ch13-multiple-lab.Rmd
+2 -2
View File
@@ -13,11 +13,11 @@ jupyter:
# Multiple Testing
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch13-multiple-lab.ipynb">
<a target="_blank" href="https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch13-multiple-lab.ipynb">
<img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/>
</a>
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch13-multiple-lab.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch13-multiple-lab.ipynb)
Ch13-multiple-lab.ipynb
+133 -134
View File
@@ -7,11 +7,11 @@
"source": [
"# Multiple Testing\n",
"\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2/Ch13-multiple-lab.ipynb\">\n",
"<a target=\"_blank\" href=\"https://colab.research.google.com/github/intro-stat-learning/ISLP_labs/blob/v2.2.1/Ch13-multiple-lab.ipynb\">\n",
"<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n",
"</a>\n",
"\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2?labpath=Ch13-multiple-lab.ipynb)\n",
"[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/intro-stat-learning/ISLP_labs/v2.2.1?labpath=Ch13-multiple-lab.ipynb)\n",
"\n",
"\n",
" "
@@ -31,10 +31,10 @@
"id": "bd52a066",
"metadata": {
"execution": {
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}
},
"outputs": [],
@@ -61,10 +61,10 @@
"id": "90117cbf",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.093032Z",
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},
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},
@@ -100,10 +100,10 @@
"id": "db60f055",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.095939Z",
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"shell.execute_reply": "2026-02-02T23:40:42.565023Z"
}
},
"outputs": [],
@@ -130,10 +130,10 @@
"id": "2f769e32",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.098889Z",
"iopub.status.busy": "2025-04-03T19:32:53.098816Z",
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"iopub.execute_input": "2026-02-02T23:40:42.566311Z",
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"shell.execute_reply": "2026-02-02T23:40:42.569565Z"
}
},
"outputs": [
@@ -177,10 +177,10 @@
"id": "662e8a87",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.103079Z",
"iopub.status.busy": "2025-04-03T19:32:53.103010Z",
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"shell.execute_reply": "2025-04-03T19:32:53.121347Z"
"iopub.execute_input": "2026-02-02T23:40:42.570975Z",
"iopub.status.busy": "2026-02-02T23:40:42.570881Z",
"iopub.status.idle": "2026-02-02T23:40:42.590875Z",
"shell.execute_reply": "2026-02-02T23:40:42.590643Z"
},
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},
@@ -213,10 +213,10 @@
"id": "b25f9969",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.122771Z",
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"iopub.status.idle": "2025-04-03T19:32:53.129771Z",
"shell.execute_reply": "2025-04-03T19:32:53.129510Z"
"iopub.execute_input": "2026-02-02T23:40:42.592212Z",
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},
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},
@@ -314,10 +314,10 @@
"id": "4c158b0b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.130993Z",
"iopub.status.busy": "2025-04-03T19:32:53.130922Z",
"iopub.status.idle": "2025-04-03T19:32:53.151941Z",
"shell.execute_reply": "2025-04-03T19:32:53.151731Z"
"iopub.execute_input": "2026-02-02T23:40:42.601626Z",
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},
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},
@@ -426,16 +426,16 @@
"id": "093264ed",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.153230Z",
"iopub.status.busy": "2025-04-03T19:32:53.153148Z",
"iopub.status.idle": "2025-04-03T19:32:53.319180Z",
"shell.execute_reply": "2025-04-03T19:32:53.318528Z"
"iopub.execute_input": "2026-02-02T23:40:42.626420Z",
"iopub.status.busy": "2026-02-02T23:40:42.626339Z",
"iopub.status.idle": "2026-02-02T23:40:42.833591Z",
"shell.execute_reply": "2026-02-02T23:40:42.832647Z"
}
},
"outputs": [
{
"data": {
"image/png": "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 truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
@@ -482,10 +482,10 @@
"id": "1a3ac106",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.323056Z",
"iopub.status.busy": "2025-04-03T19:32:53.322678Z",
"iopub.status.idle": "2025-04-03T19:32:53.356260Z",
"shell.execute_reply": "2025-04-03T19:32:53.355323Z"
"iopub.execute_input": "2026-02-02T23:40:42.838668Z",
"iopub.status.busy": "2026-02-02T23:40:42.838263Z",
"iopub.status.idle": "2026-02-02T23:40:42.909564Z",
"shell.execute_reply": "2026-02-02T23:40:42.909245Z"
}
},
"outputs": [
@@ -550,10 +550,10 @@
"id": "b9f1eac7",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.359943Z",
"iopub.status.busy": "2025-04-03T19:32:53.359613Z",
"iopub.status.idle": "2025-04-03T19:32:53.367392Z",
"shell.execute_reply": "2025-04-03T19:32:53.366785Z"
"iopub.execute_input": "2026-02-02T23:40:42.911009Z",
"iopub.status.busy": "2026-02-02T23:40:42.910932Z",
"iopub.status.idle": "2026-02-02T23:40:42.913088Z",
"shell.execute_reply": "2026-02-02T23:40:42.912887Z"
},
"lines_to_next_cell": 2
},
@@ -589,10 +589,10 @@
"id": "0cee9c30",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.370653Z",
"iopub.status.busy": "2025-04-03T19:32:53.370309Z",
"iopub.status.idle": "2025-04-03T19:32:53.377086Z",
"shell.execute_reply": "2025-04-03T19:32:53.376491Z"
"iopub.execute_input": "2026-02-02T23:40:42.914211Z",
"iopub.status.busy": "2026-02-02T23:40:42.914139Z",
"iopub.status.idle": "2026-02-02T23:40:42.916323Z",
"shell.execute_reply": "2026-02-02T23:40:42.916073Z"
}
},
"outputs": [
@@ -631,10 +631,10 @@
"id": "1f7cee90",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.381069Z",
"iopub.status.busy": "2025-04-03T19:32:53.380804Z",
"iopub.status.idle": "2025-04-03T19:32:53.429473Z",
"shell.execute_reply": "2025-04-03T19:32:53.428127Z"
"iopub.execute_input": "2026-02-02T23:40:42.917445Z",
"iopub.status.busy": "2026-02-02T23:40:42.917375Z",
"iopub.status.idle": "2026-02-02T23:40:42.957649Z",
"shell.execute_reply": "2026-02-02T23:40:42.957396Z"
},
"lines_to_next_cell": 2
},
@@ -671,10 +671,10 @@
"id": "59cdfe23",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.432686Z",
"iopub.status.busy": "2025-04-03T19:32:53.432364Z",
"iopub.status.idle": "2025-04-03T19:32:53.435417Z",
"shell.execute_reply": "2025-04-03T19:32:53.435162Z"
"iopub.execute_input": "2026-02-02T23:40:42.958881Z",
"iopub.status.busy": "2026-02-02T23:40:42.958809Z",
"iopub.status.idle": "2026-02-02T23:40:42.961378Z",
"shell.execute_reply": "2026-02-02T23:40:42.961187Z"
},
"lines_to_next_cell": 2
},
@@ -715,10 +715,10 @@
"id": "bf01100e",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.436763Z",
"iopub.status.busy": "2025-04-03T19:32:53.436655Z",
"iopub.status.idle": "2025-04-03T19:32:53.439076Z",
"shell.execute_reply": "2025-04-03T19:32:53.438865Z"
"iopub.execute_input": "2026-02-02T23:40:42.962467Z",
"iopub.status.busy": "2026-02-02T23:40:42.962393Z",
"iopub.status.idle": "2026-02-02T23:40:42.964706Z",
"shell.execute_reply": "2026-02-02T23:40:42.964522Z"
}
},
"outputs": [
@@ -767,10 +767,10 @@
"id": "60146e08",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.440229Z",
"iopub.status.busy": "2025-04-03T19:32:53.440124Z",
"iopub.status.idle": "2025-04-03T19:32:53.833595Z",
"shell.execute_reply": "2025-04-03T19:32:53.833313Z"
"iopub.execute_input": "2026-02-02T23:40:42.965724Z",
"iopub.status.busy": "2026-02-02T23:40:42.965661Z",
"iopub.status.idle": "2026-02-02T23:40:43.337336Z",
"shell.execute_reply": "2026-02-02T23:40:43.337101Z"
},
"lines_to_next_cell": 2
},
@@ -827,16 +827,16 @@
"id": "2ec0aae4",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.834950Z",
"iopub.status.busy": "2025-04-03T19:32:53.834875Z",
"iopub.status.idle": "2025-04-03T19:32:53.877086Z",
"shell.execute_reply": "2025-04-03T19:32:53.876823Z"
"iopub.execute_input": "2026-02-02T23:40:43.338635Z",
"iopub.status.busy": "2026-02-02T23:40:43.338557Z",
"iopub.status.idle": "2026-02-02T23:40:43.400697Z",
"shell.execute_reply": "2026-02-02T23:40:43.400471Z"
}
},
"outputs": [
{
"data": {
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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 1000x600 with 1 Axes>"
]
@@ -868,10 +868,10 @@
"id": "1de94dbc",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:53.878355Z",
"iopub.status.busy": "2025-04-03T19:32:53.878280Z",
"iopub.status.idle": "2025-04-03T19:32:54.189626Z",
"shell.execute_reply": "2025-04-03T19:32:54.189218Z"
"iopub.execute_input": "2026-02-02T23:40:43.401915Z",
"iopub.status.busy": "2026-02-02T23:40:43.401843Z",
"iopub.status.idle": "2026-02-02T23:40:43.724524Z",
"shell.execute_reply": "2026-02-02T23:40:43.724263Z"
}
},
"outputs": [],
@@ -897,10 +897,10 @@
"id": "b0aa032c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.191140Z",
"iopub.status.busy": "2025-04-03T19:32:54.191057Z",
"iopub.status.idle": "2025-04-03T19:32:54.193550Z",
"shell.execute_reply": "2025-04-03T19:32:54.193343Z"
"iopub.execute_input": "2026-02-02T23:40:43.726078Z",
"iopub.status.busy": "2026-02-02T23:40:43.725996Z",
"iopub.status.idle": "2026-02-02T23:40:43.728507Z",
"shell.execute_reply": "2026-02-02T23:40:43.728266Z"
}
},
"outputs": [
@@ -942,10 +942,10 @@
"id": "ba6dcb50",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.194685Z",
"iopub.status.busy": "2025-04-03T19:32:54.194612Z",
"iopub.status.idle": "2025-04-03T19:32:54.196704Z",
"shell.execute_reply": "2025-04-03T19:32:54.196500Z"
"iopub.execute_input": "2026-02-02T23:40:43.729744Z",
"iopub.status.busy": "2026-02-02T23:40:43.729667Z",
"iopub.status.idle": "2026-02-02T23:40:43.732002Z",
"shell.execute_reply": "2026-02-02T23:40:43.731704Z"
},
"lines_to_next_cell": 0
},
@@ -986,10 +986,10 @@
"id": "44c1b26a",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.197806Z",
"iopub.status.busy": "2025-04-03T19:32:54.197720Z",
"iopub.status.idle": "2025-04-03T19:32:54.199706Z",
"shell.execute_reply": "2025-04-03T19:32:54.199496Z"
"iopub.execute_input": "2026-02-02T23:40:43.733204Z",
"iopub.status.busy": "2026-02-02T23:40:43.733131Z",
"iopub.status.idle": "2026-02-02T23:40:43.735178Z",
"shell.execute_reply": "2026-02-02T23:40:43.734967Z"
},
"lines_to_next_cell": 2
},
@@ -1036,10 +1036,10 @@
"id": "f23a1f9f",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.200867Z",
"iopub.status.busy": "2025-04-03T19:32:54.200798Z",
"iopub.status.idle": "2025-04-03T19:32:54.203144Z",
"shell.execute_reply": "2025-04-03T19:32:54.202843Z"
"iopub.execute_input": "2026-02-02T23:40:43.736262Z",
"iopub.status.busy": "2026-02-02T23:40:43.736193Z",
"iopub.status.idle": "2026-02-02T23:40:43.738272Z",
"shell.execute_reply": "2026-02-02T23:40:43.738070Z"
}
},
"outputs": [],
@@ -1070,17 +1070,17 @@
"id": "3c3018cc",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.204649Z",
"iopub.status.busy": "2025-04-03T19:32:54.204557Z",
"iopub.status.idle": "2025-04-03T19:32:54.353161Z",
"shell.execute_reply": "2025-04-03T19:32:54.352863Z"
"iopub.execute_input": "2026-02-02T23:40:43.739348Z",
"iopub.status.busy": "2026-02-02T23:40:43.739279Z",
"iopub.status.idle": "2026-02-02T23:40:43.914663Z",
"shell.execute_reply": "2026-02-02T23:40:43.914426Z"
},
"lines_to_next_cell": 2
},
"outputs": [
{
"data": {
"image/png": 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truncated
"image/png": 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truncated
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
@@ -1120,10 +1120,10 @@
"id": "d49b3de7",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.354663Z",
"iopub.status.busy": "2025-04-03T19:32:54.354563Z",
"iopub.status.idle": "2025-04-03T19:32:54.405469Z",
"shell.execute_reply": "2025-04-03T19:32:54.405244Z"
"iopub.execute_input": "2026-02-02T23:40:43.916217Z",
"iopub.status.busy": "2026-02-02T23:40:43.916122Z",
"iopub.status.idle": "2026-02-02T23:40:43.973817Z",
"shell.execute_reply": "2026-02-02T23:40:43.973588Z"
},
"lines_to_next_cell": 2
},
@@ -1131,12 +1131,11 @@
{
"data": {
"text/plain": [
"Y\n",
"2 29\n",
"4 25\n",
"3 18\n",
"1 11\n",
"Name: count, dtype: int64"
"Name: Y, dtype: int64"
]
},
"execution_count": 23,
@@ -1172,10 +1171,10 @@
"id": "18eaeb65",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.406764Z",
"iopub.status.busy": "2025-04-03T19:32:54.406668Z",
"iopub.status.idle": "2025-04-03T19:32:54.410015Z",
"shell.execute_reply": "2025-04-03T19:32:54.409790Z"
"iopub.execute_input": "2026-02-02T23:40:43.975057Z",
"iopub.status.busy": "2026-02-02T23:40:43.974970Z",
"iopub.status.idle": "2026-02-02T23:40:43.978337Z",
"shell.execute_reply": "2026-02-02T23:40:43.978117Z"
},
"lines_to_next_cell": 2
},
@@ -1225,10 +1224,10 @@
"id": "8e2f821c",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:54.411194Z",
"iopub.status.busy": "2025-04-03T19:32:54.411115Z",
"iopub.status.idle": "2025-04-03T19:32:56.102203Z",
"shell.execute_reply": "2025-04-03T19:32:56.101891Z"
"iopub.execute_input": "2026-02-02T23:40:43.979564Z",
"iopub.status.busy": "2026-02-02T23:40:43.979493Z",
"iopub.status.idle": "2026-02-02T23:40:45.736220Z",
"shell.execute_reply": "2026-02-02T23:40:45.735978Z"
},
"lines_to_next_cell": 2
},
@@ -1276,17 +1275,17 @@
"id": "f10d3bf0",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:56.103547Z",
"iopub.status.busy": "2025-04-03T19:32:56.103471Z",
"iopub.status.idle": "2025-04-03T19:32:56.242320Z",
"shell.execute_reply": "2025-04-03T19:32:56.242062Z"
"iopub.execute_input": "2026-02-02T23:40:45.737603Z",
"iopub.status.busy": "2026-02-02T23:40:45.737525Z",
"iopub.status.idle": "2026-02-02T23:40:45.904098Z",
"shell.execute_reply": "2026-02-02T23:40:45.903787Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAqgAAAKnCAYAAABK7r+JAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjEsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvc2/+5QAAAAlwSFlzAAAPYQAAD2EBqD+naQAAcmFJREFUeJzt3Qd4lfX9/vE7g5AdlkxBprIElCUOxBbFUatWLfq3RanF1vGr1lpHraDVFnetimBV6laqVTpUHGhwMQREkCUoyIYwkpAEsv/X53lyQgIJJCHJ94z367rOdZ5zcs5zPkkO5D7fGVVaWloqAAAAIEhEuy4AAAAAqIiACgAAgKBCQAUAAEBQIaACAAAgqBBQAQAAEFQIqAAAAAgqBFQAAAAEFQIqAAAAgkqswkBJSYk2bdqklJQURUVFuS4HAAAA+7G9oXbv3q327dsrOjo6/AOqhdOOHTu6LgMAAACHsH79eh155JHhH1Ct5TTwDaemprouB6i13FypfXv/eNMmKSnJdUUAANSv7Oxsr0ExkNvCPqAGuvUtnBJQEYpiYvYd21uYgAoACFc1GY7JJCkAAAAEFQIqAAAAggoBFQAAAEElLMagAgCA0F+CqKioSMXFxa5LwWGIiYlRbGzsYS/7SUAFAABOFRQUaPPmzcrLy3NdCupBYmKi2rVrp7i4uDqfg4AKAACcbrazZs0ar+XNFnC3UMOmO6HbCm4fNjIyMrzfaY8ePQ65IH91CKgAAMAZCzQWUm19TGt5Q2hLSEhQkyZN9P3333u/2/j4+Dqdh0lSAADAubq2tCE8f5e8GwAAABBUCKgAAAAOXXHFFTr//PPLb48YMUI33HCDIhljUAEAQNBJT2/ciVIjRpTWKVg+99xzmjhxom699dby+6dPn64LLrjAmzSEuqEFFQAAoI5sEtB9992nXbt2uS4lrBBQAQAA6mjkyJFq27at14palTvvvFMDBgyodN8jjzyizp07N1KFoYmACgAAUEe2futf/vIXPfbYY9qwYYPrcsIGARUAAOAw2HhTayWdMGGC61LCBgEVAADgMNk4VJswtXz5ctelhAUCKgAAwGEaPny4Ro0apdtuu+2ARev3n81fWFjYyNWFHpaZAgAAqAf33nuv19V/zDHHlN93xBFHaMuWLV5IjYryl85atGiRwypDAy2oAAAA9eDYY4/VZZddpkcffbTSovsZGRm6//779e2332rSpEl65513nNYZCgioAAAA9eRPf/qTSkpKym/36tVLTzzxhBdM+/fvr3nz5ummm25yWmMoiCoNg20OsrOzlZaWpqysLKWmprouB6i13FwpOdk/zsmRkpJcVwQAjWPv3r1as2aNunTp4i16j9BX3e+0NnmNFlQAAAAEFQIqAAAAggoBFQAAAEGFgAoAAICgQkAFAABAUGGhfgCIIOnp/kLhFY0YEfKLuQAIM7SgAgAAIKgQUAEAABBU6OIHgBBHtz2AcEMLKgAAQAPq3LmzHnnkEYWLzo3w/RBQAQAA6mj9+vX6xS9+ofbt2ysuLk5HHXWUrr/+eu3YscN1aSGNgAoAAFAH3333nQYNGqRVq1bplVde0erVqzVlyhTNnDlTw4YN086dO53UVVxcrJKSEoUyAioAAEAdXHvttV6r6XvvvadTTz1VnTp10llnnaUPPvhAGzdu1O23317+2N27d+vSSy9VUlKSOnTooEmTJpV/rbS0VHfeeaf3/KZNm3qtsb/5zW/Kv56fn6+bbrrJe549f+jQoUpPTy//+rPPPqtmzZrpP//5j3r37u2d4+mnn1Z8fLwyMzMr1Wytuz/4wQ/Kb3/66ac65ZRTlJCQoI4dO3qvm5ubW/71bdu26dxzz/W+3qVLF7300ktqDARUAAAQNEpLJctHLi722jVlraPvvvuurrnmGi+8VdS2bVtddtllmjZtmhc+zQMPPKD+/fvryy+/1K233uoFxffff9/72r/+9S/99a9/1ZNPPum1xk6fPl3HHnts+fmuu+46zZ49W6+++qoWL16siy++WGeeeab32IC8vDzdd999XjBdunSp9/oWWu3cFVtWrSb7mvn222+981x44YXeee1rFljt9QKuuOIKbxjDRx99pNdff11PPPGEF1obGrP4AQBA0MjLk5KT3bx2To6UlFSzx1o4tPDZq1evKr9u9+/atUsZGRne7ZNOOskLpuboo4/WZ5995oXS008/XevWrfNC7ciRI9WkSROvJXXIkCHeY+1r//jHP7xra1k11po6Y8YM7/6//OUv3n2FhYVeeLQQHHDJJZfo5Zdf1pVXXundtqEH1qJqgdRMnDjRC6s33HCDd7tHjx569NFHvdbgyZMne6/5zjvvaN68eRo8eLD3mGeeeaba77k+0YIKAABQR4EW0kOxMan7316+fLl3bC2ie/bsUdeuXTVu3Di9+eabKioq8r62ZMkSr+XTQm1ycnL5ZdasWV4LaIANNejXr1+l17DwaUMBNm3a5N227vlzzjnHa1k1X331lTc8oOJ5R40a5Y1fXbNmjVdfbGysBg4cWH7Onj17lj+/IdGCCgAAgkZiot+S6eq1a6p79+6KioryQtwFF1xwwNft/ubNm+uII4445Lls7OfKlSu9savW7X/NNdd4QwIshObk5CgmJkYLFizwriuyQBlgwwysnoqs1bNbt27e0ICrr77aC74WSAPs3L/61a8qjXcNsFbcb775Rq4QUAEAQNCwjFXTbnaXWrZs6XXPW7f6b3/720rjULds2eK1Vo4ZM6Y8NM6ZM6fS8+12xa5ye75NRrLLtdde67VUWuvpcccd57Wg2rhPm8xUW9aKarUceeSRio6O9lpQA44//ngtW7bMC9tVsRqsJdfCcaCL34L0/hOvGgJd/AAAAHXw+OOPezPsrVv8448/9iYT2dhQC6424/7Pf/5z+WNtzOn999/vtUraDP7XXnvNmyhlrFXTxnZ+/fXX3tJVL774ohdYbU1V69q3kGlh94033vC63m1MqI0ffeuttw5Zoz134cKFXi0XXXSRN8M/4JZbbtHnn3/uTYpatGiRN6723//+d/kkqWOOOcabRGWtrHPnzvWC6i9/+csDJoU1BAIqAABAHdikovnz53tjR3/605963elXXXWVTjvtNG/WfYsWLcof+7vf/c57rLWI3nPPPXr44Ye9YGtsTOdTTz3lTaSycaQffPCB/vvf/3qttMYmQ1lAtXNYaDz//PP1xRdfeN3wh2KtozbhymbpB2bvB9hr2TACC83WOmu1jR8/vnwyVuC17bZNnPrJT37ifX+tW7dWQ4sqreno3iCWnZ2ttLQ0ZWVlKTU11XU5QK3Z8iaBoUS1mUUKmPT0yuPOzIgRpYf9WKAx7N2712sVtDU2bd1OhL7qfqe1yWu0oAIAACCoEFABAAAQVAioAAAACCoEVAAAAAQVAioAAACCCgEVAAA4FwaLCqEef5cEVAAA4EyTJk2867y8PNeloJ4EfpeB321dsNUpAABwxvaXt4XqbStPk5iYeMCe8gidllMLp/a7tN+p/W7rioAKAI2gqgXyDYvkA1Lbtm2960BIRWizcBr4ndYVARUAADhlLabt2rXzttAsLCx0XQ4Og3XrH07LaQABFQAABAULNvURbhD6mCQFAACAoEJABQAAQFAhoAIAACCoEFABAAAQVAioAAAACCoEVAAAAIR+QJ00aZI6d+6s+Ph4DR06VPPmzavR81599VVvrbPzzz//gJ0Hxo8f762BlpCQoJEjR2rVqlV1KQ0AAACRFlCnTZumG2+8URMmTNDChQvVv39/jRo16pC7P6xdu1Y33XSTTjnllAO+dv/99+vRRx/VlClTNHfuXCUlJXnn3Lt3b23LAwAAQKQF1Icffljjxo3T2LFj1bt3by9U2r65U6dOrfY5xcXFuuyyy3TXXXepa9euB7SePvLII/rjH/+o8847T/369dPzzz+vTZs2afr06XX7rgAAABAZAbWgoEALFizwuuDLTxAd7d2ePXt2tc/705/+5G1fduWVVx7wtTVr1mjLli2VzpmWluYNHajunPn5+crOzq50AQAAQAQG1O3bt3utoW3atKl0v922kFmVTz/9VM8884yeeuqpKr8eeF5tzjlx4kQvxAYuHTt2rM23AQAAgEidxb979279/Oc/98Jpq1at6u28t912m7Kyssov69evr7dzAwAAwK3Y2jzYQmZMTIy2bt1a6X673bZt2wMe/+2333qTo84999zy+0pKSvwXjo3VypUry59n57BZ/BXPOWDAgCrraNq0qXcBgHCUnh5V5f0jRpTaGCcbvC/Fxzd6XQAQlC2ocXFxGjhwoGbOnFkpcNrtYcOGHfD4nj17asmSJVq0aFH55cc//rFOO+0079i65rt06eKF1IrntDGlNpu/qnMCQCSJKpJafSr1uUNS69Z+ME1IkFq2lH70I+mFFxRV6LpKAHDYgmpsianLL79cgwYN0pAhQ7wZ+Lm5ud6sfjNmzBh16NDBGydq66T27du30vObNWvmXVe8/4YbbtA999yjHj16eIH1jjvuUPv27Q9YLxUAIknzeVKPx6TEDYF7MvZ9cedO6a23vMuQ9tJ3V0kZpzoqFABcB9TRo0crIyPDW1jfJjFZN/yMGTPKJzmtW7fOm9lfGzfffLMXcq+66iplZmbq5JNP9s5pARcAIq0731pEuz8udfiPf7sgTdpyltTphjnSMcdIUVHS6tV+QH3iCSVs2qo+d0qbz5RW/UYqSWj87wMA6lNUqS1EGuJsSIDN5rcJU6mpqa7LAWotN1dKTvaPc3KkpCTXFaGxxpXuLyZHOvZ2qdliqTRK2nChtPYKqTipbAzq/nJztfbqZB31khRVImX3lBbfJ53849Ia11HleQHAYV5r0Fn8AICai8mT+t3qh9OiJGnJn6Vvr/XDabWSkrT2F9JXD0mFqVLqCmnADTYaoMJwAAAIMQRUAAiSyVB9/yilLZUKU6RFj0gLine truncated
"image/png": "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 truncated
"text/plain": [
"<Figure size 800x800 with 1 Axes>"
]
@@ -1336,10 +1335,10 @@
"id": "d37287ae",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:32:56.243677Z",
"iopub.status.busy": "2025-04-03T19:32:56.243581Z",
"iopub.status.idle": "2025-04-03T19:35:57.109614Z",
"shell.execute_reply": "2025-04-03T19:35:57.109250Z"
"iopub.execute_input": "2026-02-02T23:40:45.905463Z",
"iopub.status.busy": "2026-02-02T23:40:45.905362Z",
"iopub.status.idle": "2026-02-02T23:43:41.101404Z",
"shell.execute_reply": "2026-02-02T23:43:41.100635Z"
}
},
"outputs": [],
@@ -1382,10 +1381,10 @@
"id": "ecaf03eb",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:35:57.111340Z",
"iopub.status.busy": "2025-04-03T19:35:57.111258Z",
"iopub.status.idle": "2025-04-03T19:35:57.218314Z",
"shell.execute_reply": "2025-04-03T19:35:57.218027Z"
"iopub.execute_input": "2026-02-02T23:43:41.106109Z",
"iopub.status.busy": "2026-02-02T23:43:41.105886Z",
"iopub.status.idle": "2026-02-02T23:43:41.236604Z",
"shell.execute_reply": "2026-02-02T23:43:41.236326Z"
}
},
"outputs": [],
@@ -1423,10 +1422,10 @@
"id": "ceacd8b8",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:35:57.219806Z",
"iopub.status.busy": "2025-04-03T19:35:57.219728Z",
"iopub.status.idle": "2025-04-03T19:35:57.222043Z",
"shell.execute_reply": "2025-04-03T19:35:57.221848Z"
"iopub.execute_input": "2026-02-02T23:43:41.238163Z",
"iopub.status.busy": "2026-02-02T23:43:41.238070Z",
"iopub.status.idle": "2026-02-02T23:43:41.241062Z",
"shell.execute_reply": "2026-02-02T23:43:41.240834Z"
}
},
"outputs": [
@@ -1478,10 +1477,10 @@
"id": "2434f370",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:35:57.223240Z",
"iopub.status.busy": "2025-04-03T19:35:57.223171Z",
"iopub.status.idle": "2025-04-03T19:35:57.225253Z",
"shell.execute_reply": "2025-04-03T19:35:57.225057Z"
"iopub.execute_input": "2026-02-02T23:43:41.242193Z",
"iopub.status.busy": "2026-02-02T23:43:41.242118Z",
"iopub.status.idle": "2026-02-02T23:43:41.244401Z",
"shell.execute_reply": "2026-02-02T23:43:41.244188Z"
}
},
"outputs": [
@@ -1546,17 +1545,17 @@
"id": "34d6a02b",
"metadata": {
"execution": {
"iopub.execute_input": "2025-04-03T19:35:57.226335Z",
"iopub.status.busy": "2025-04-03T19:35:57.226270Z",
"iopub.status.idle": "2025-04-03T19:35:57.263024Z",
"shell.execute_reply": "2025-04-03T19:35:57.262794Z"
"iopub.execute_input": "2026-02-02T23:43:41.245792Z",
"iopub.status.busy": "2026-02-02T23:43:41.245713Z",
"iopub.status.idle": "2026-02-02T23:43:41.304373Z",
"shell.execute_reply": "2026-02-02T23:43:41.304028Z"
},
"lines_to_next_cell": 0
},
"outputs": [
{
"data": {
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truncated
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truncated
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
@@ -1597,7 +1596,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
"version": "3.11.4"
}
},
"nbformat": 4,
requirements.txt
+2 -1
View File
@@ -1,4 +1,5 @@
numpy==2.4.2
numpy==2.3.5
numba==0.63.1
scipy==1.16.3
pandas==3.0.0
lxml==6.0.2