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tteofili/pdp_example.ipynb

Last active December 13, 2022 10:15
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TrustyAI PDP Example Notebook
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pdp_example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "e4c8a080",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"SLF4J: Failed to load class \"org.slf4j.impl.StaticLoggerBinder\".\n",
"SLF4J: Defaulting to no-operation (NOP) logger implementation\n",
"SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.\n"
]
}
],
"source": [
"from trustyai.model import feature, PredictionInput\n",
"from trustyai.utils import TestModels\n",
"from trustyai.explainers.pdp import PDPExplainer, PredictionProviderMetadata\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from sklearn.datasets import make_classification"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "551b8be4",
"metadata": {},
"outputs": [],
"source": [
"model = TestModels.getSumSkipModel(0)\n",
"\n",
"no_of_features = 5\n",
"data = []\n",
"for i in range(100):\n",
" data.append(PredictionInput([feature(name=f\"f-num{i}\", value=np.random.randint(-100, 100), dtype=\"number\") for i in range(no_of_features)]))"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "074e91f4",
"metadata": {},
"outputs": [],
"source": [
"pdp_explainer = PDPExplainer()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "0a77ea32",
"metadata": {},
"outputs": [],
"source": [
"pdp_results = pdp_explainer.explain(model, data)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d7d7b739",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>-100.0</th>\n",
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" <th>-93.0</th>\n",
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" <th>-70.0</th>\n",
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" <th>-63.0</th>\n",
" <th>...</th>\n",
" <th>-45.0</th>\n",
" <th>-40.0</th>\n",
" <th>-38.0</th>\n",
" <th>-22.0</th>\n",
" <th>20.0</th>\n",
" <th>56.0</th>\n",
" <th>64.0</th>\n",
" <th>85.0</th>\n",
" <th>87.0</th>\n",
" <th>95.0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>7.27</td>\n",
" <td>7.27</td>\n",
" <td>7.27</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>-79.24</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-81.35</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-94.81</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-81.81</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
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" <td>-39.81</td>\n",
" <td>-34.81</td>\n",
" <td>-32.81</td>\n",
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" <td>25.19</td>\n",
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" <td>69.19</td>\n",
" <td>90.19</td>\n",
" <td>92.19</td>\n",
" <td>100.19</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 156 columns</p>\n",
"</div>"
],
"text/plain": [
" -100.0 -98.0 -93.0 -89.0 -87.0 -73.0 -72.0 -70.0 -65.0 \\\n",
"0 7.27 7.27 7.27 7.27 7.27 7.27 7.27 7.27 7.27 \n",
"1 NaN -79.24 NaN NaN NaN NaN -53.24 NaN NaN \n",
"2 NaN -81.79 NaN NaN NaN NaN NaN NaN -48.79 \n",
"3 NaN NaN NaN NaN -105.35 NaN NaN NaN NaN \n",
"4 -94.81 NaN NaN NaN -81.81 NaN NaN NaN NaN \n",
"\n",
" -63.0 ... -45.0 -40.0 -38.0 -22.0 20.0 56.0 64.0 \\\n",
"0 7.27 ... NaN NaN NaN NaN NaN NaN NaN \n",
"1 NaN ... NaN NaN NaN NaN NaN NaN NaN \n",
"2 NaN ... NaN NaN NaN NaN NaN NaN NaN \n",
"3 -81.35 ... NaN NaN NaN NaN NaN NaN NaN \n",
"4 NaN ... -39.81 -34.81 -32.81 -16.81 25.19 61.19 69.19 \n",
"\n",
" 85.0 87.0 95.0 \n",
"0 NaN NaN NaN \n",
"1 NaN NaN NaN \n",
"2 NaN NaN NaN \n",
"3 NaN NaN NaN \n",
"4 90.19 92.19 100.19 \n",
"\n",
"[5 rows x 156 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pdp_results.as_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "3ee0dfd6",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 640x480 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"pdp_results.plot()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "1e3898c5",
"metadata": {},
"outputs": [],
"source": [
"def create_random_dataframe_classifier():\n",
" X, _ = make_classification(n_samples=5000, n_features=5, n_classes=2,\n",
" n_clusters_per_class=2, class_sep=2, flip_y=0, random_state=23)\n",
"\n",
" return pd.DataFrame({\n",
" 'x1': X[:, 0],\n",
" 'x2': X[:, 1],\n",
" 'x3': X[:, 2],\n",
" 'x4': X[:, 3],\n",
" 'x5': X[:, 4],\n",
" })"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "73a5e496",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>x1</th>\n",
" <th>x2</th>\n",
" <th>x3</th>\n",
" <th>x4</th>\n",
" <th>x5</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>-2.124064</td>\n",
" <td>1.608138</td>\n",
" <td>-0.404920</td>\n",
" <td>0.942188</td>\n",
" <td>-2.754050</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>3.048919</td>\n",
" <td>-2.428100</td>\n",
" <td>0.427166</td>\n",
" <td>-1.466329</td>\n",
" <td>4.053088</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2.241751</td>\n",
" <td>-2.109687</td>\n",
" <td>-0.410332</td>\n",
" <td>-1.386671</td>\n",
" <td>3.250637</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3.299680</td>\n",
" <td>-1.386333</td>\n",
" <td>0.149882</td>\n",
" <td>-0.406165</td>\n",
" <td>3.351016</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2.226471</td>\n",
" <td>-0.992053</td>\n",
" <td>-0.475162</td>\n",
" <td>-0.327913</td>\n",
" <td>2.308332</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" x1 x2 x3 x4 x5\n",
"0 -2.124064 1.608138 -0.404920 0.942188 -2.754050\n",
"1 3.048919 -2.428100 0.427166 -1.466329 4.053088\n",
"2 2.241751 -2.109687 -0.410332 -1.386671 3.250637\n",
"3 3.299680 -1.386333 0.149882 -0.406165 3.351016\n",
"4 2.226471 -0.992053 -0.475162 -0.327913 2.308332"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = create_random_dataframe_classifier()\n",
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "fc2975cc",
"metadata": {},
"outputs": [],
"source": [
"class_model = TestModels.getLinearThresholdModel([0.1, 0.2, 0.3, 0.4, 0.5], 0)\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "b98c2205",
"metadata": {},
"outputs": [
{
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" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>...</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" <td>true</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows × 500 columns</p>\n",
"</div>"
],
"text/plain": [
" -3.176352 -3.007164 -2.730154 -2.725931 -2.690126 -2.637724 -2.631791 \\\n",
"0 false false false false false false false \n",
"1 NaN NaN NaN NaN NaN NaN NaN \n",
"2 NaN NaN NaN NaN NaN NaN NaN \n",
"3 NaN NaN NaN NaN NaN NaN NaN \n",
"4 NaN NaN NaN NaN NaN NaN NaN \n",
"\n",
" -2.608869 -2.595924 -2.522616 ... 2.972526 3.091173 3.120251 3.268394 \\\n",
"0 false false false ... NaN NaN NaN NaN \n",
"1 NaN NaN NaN ... NaN NaN NaN NaN \n",
"2 NaN NaN NaN ... NaN NaN NaN NaN \n",
"3 NaN NaN NaN ... NaN NaN NaN NaN \n",
"4 NaN NaN NaN ... true true true true \n",
"\n",
" 3.336480 3.346023 3.362623 3.468502 3.712694 3.753402 \n",
"0 NaN NaN NaN NaN NaN NaN \n",
"1 NaN NaN NaN NaN NaN NaN \n",
"2 NaN NaN NaN NaN NaN NaN \n",
"3 NaN NaN NaN NaN NaN NaN \n",
"4 true true true true true true \n",
"\n",
"[5 rows x 500 columns]"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"class_pdp_results = pdp_explainer.explain(class_model, df)\n",
"class_pdp_results.as_dataframe()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "00dd2870",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 640x480 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"class_pdp_results.plot()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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