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Andrea Gobbi committed
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "e9ca0612-adb5-4d11-89a1-b224de3bd3b5",
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"sys.path.append('../') ##accrocchio\n",
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"from src.utils import retrive_data,split\n",
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"import pickle"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dcb4d7b5-fe20-43f1-b988-51c9d595e06d",
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"metadata": {},
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"outputs": [],
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"source": [
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"labeled,labeled_small = retrive_data(False,threshold_under_represented=0.5,path='/home/agobbi/Projects/PID/datanalytics/PID/src')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "569dff52-2a78-43f4-ae40-07842d3669e3",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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" class p\n",
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"0 0 0.203424\n",
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"1 1 0.013596\n",
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"2 2 0.056109\n",
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"3 3 1.130661\n",
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"4 4 16.206137\n"
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]
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}
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],
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"source": [
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"dataset,dataset_test = split(labeled_small,\n",
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" SKI_AREA_TEST= 'Klausberg',\n",
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" SEASON_TEST_SKIAREA = 'Kronplatz',\n",
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" SEASON_TEST_YEAR= 2023,\n",
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" use_smote = False,\n",
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" weight_type = 'sqrt' )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"id": "65405081-748d-43ef-aed6-2a58e38673b4",
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"metadata": {},
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"outputs": [],
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"source": [
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"with open('../src/best_params_and_final_model.pkl','rb') as f:\n",
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" tot,bst_FS,FS = pickle.load(f) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 49,
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"id": "53434031-1a11-49f7-9481-de77f250d35b",
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"metadata": {},
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"outputs": [],
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"source": [
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"import shap\n",
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"import xgboost as xgb\n",
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"import numpy as np\n",
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"dtest_FS = xgb.DMatrix(dataset_test.X_test_area[bst_FS.feature_names],dataset_test.y_test_area,enable_categorical=True,)\n",
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"\n",
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"explainer = shap.TreeExplainer(bst_FS,feature_names=bst_FS.feature_names)\n",
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"shap_values = explainer.shap_values(dtest_FS)\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 33,
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"id": "f3b72453-27be-4db5-b40d-883454c294f9",
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"metadata": {},
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"outputs": [
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"array([2.58451770e-03, 2.63414029e-02, 8.63697469e-01, 1.07182816e-01,\n",
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" 1.93854154e-04], dtype=float32)"
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"source": [
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"pred = bst_FS.predict(dtest_FS)\n",
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"pred[2]"
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{
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"data": {
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"text/plain": [
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"age 53.0\n",
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"diagnosis dislocation\n",
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"injury_general_location upper_limbs\n",
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"country Germania\n",
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"difficulty easy\n",
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"cause fall_alone\n",
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"destination hospital_emergency_room\n",
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"injury_side R\n",
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"equipment ski\n",
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"gender F\n",
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"snowmobile True\n",
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"helicopter True\n",
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"akja False\n",
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"helmet True\n",
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"ambulance False\n",
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"snowmobile_sled False\n",
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"ski_lift False\n",
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"indipendently False\n",
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"skiarea_ambulance False\n",
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"other False\n",
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"Name: 724, dtype: object"
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]
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"output_type": "execute_result"
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}
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],
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"source": [
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"dataset_test.X_test_area[bst_FS.feature_names].iloc[2]"
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"dataset_test.y_test_area.iloc[2]"
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"source": [
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"[shap_values[i][2].sum() for i in range(5)]"
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|
||||
" <b>Visualization omitted, Javascript library not loaded!</b><br>\n",
|
||||
" Have you run `initjs()` in this notebook? If this notebook was from another\n",
|
||||
" user you must also trust this notebook (File -> Trust notebook). If you are viewing\n",
|
||||
" this notebook on github the Javascript has been stripped for security. If you are using\n",
|
||||
" JupyterLab this error is because a JupyterLab extension has not yet been written.\n",
|
||||
"</div></div>\n",
|
||||
" <script>\n",
|
||||
" if (window.SHAP) SHAP.ReactDom.render(\n",
|
||||
" SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"f(x)\"], \"baseValue\": 0.552638053894043, \"outValue\": 2.445746421813965, \"link\": \"identity\", \"featureNames\": [\"age\", \"diagnosis\", \"injury_general_location\", \"country\", \"difficulty\", \"cause\", \"destination\", \"injury_side\", \"equipment\", \"gender\", \"snowmobile\", \"helicopter\", \"akja\", \"helmet\", \"ambulance\", \"snowmobile_sled\", \"ski_lift\", \"indipendently\", \"skiarea_ambulance\", \"other\"], \"features\": {\"0\": {\"effect\": 0.16000449657440186, \"value\": \"\"}, \"1\": {\"effect\": 0.44064590334892273, \"value\": \"\"}, \"2\": {\"effect\": 0.3827016353607178, \"value\": \"\"}, \"3\": {\"effect\": 0.05334072560071945, \"value\": \"\"}, \"4\": {\"effect\": 0.17687170207500458, \"value\": \"\"}, \"5\": {\"effect\": 0.046136993914842606, \"value\": \"\"}, \"6\": {\"effect\": 0.362857460975647, \"value\": \"\"}, \"7\": {\"effect\": 0.1898631602525711, \"value\": \"\"}, \"8\": {\"effect\": 0.039788179099559784, \"value\": \"\"}, \"9\": {\"effect\": -0.024055209010839462, \"value\": \"\"}, \"10\": {\"effect\": 0.2057642787694931, \"value\": \"\"}, \"11\": {\"effect\": 0.08326093852519989, \"value\": \"\"}, \"12\": {\"effect\": -0.0021338891237974167, \"value\": \"\"}, \"13\": {\"effect\": -0.011541801504790783, \"value\": \"\"}, \"14\": {\"effect\": -0.12199775129556656, \"value\": \"\"}, \"15\": {\"effect\": -0.08116263896226883, \"value\": \"\"}, \"16\": {\"effect\": -0.030168458819389343, \"value\": \"\"}, \"17\": {\"effect\": 0.021043526008725166, \"value\": \"\"}, \"18\": {\"effect\": -0.0011919558746740222, \"value\": \"\"}, \"19\": {\"effect\": 0.003081258852034807, \"value\": \"\"}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n",
|
||||
" document.getElementById('iOOXREDIO2XGF7NOS1QU8')\n",
|
||||
" );\n",
|
||||
"</script>"
|
||||
],
|
||||
"text/plain": [
|
||||
"<shap.plots._force.AdditiveForceVisualizer at 0x7fb5822b3190>"
|
||||
]
|
||||
},
|
||||
"execution_count": 70,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"i=2\n",
|
||||
"shap.plots.force(explainer.expected_value[1], shap_values[i][2],feature_names=bst_FS.feature_names)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "6bbece5c-75f4-4ba0-a44e-677d9819b17a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"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": "3.11.0"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Reference in new issue
Block a user