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Merged
SalimM21 merged 1 commit into from
Oct 31, 2025
Merged

Exemple d’un batch de test #12

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Expand All @@ -359,13 +359,29 @@
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Expand All @@ -387,20 +403,26 @@
" <thead>\n",
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Expand All @@ -411,22 +433,22 @@
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{
"ename": "KeyError",
"evalue": "'metrics.f1'",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mKeyError\u001b[39m Traceback (most recent call last)",
"\u001b[32m~\\AppData\\Local\\Temp\\ipykernel_15856\\758707258.py\u001b[39m in \u001b[36m?\u001b[39m\u001b[34m()\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m best_run = runs.sort_values(\u001b[33m\"metrics.f1\"\u001b[39m, ascending=\u001b[38;5;28;01mFalse\u001b[39;00m).iloc[\u001b[32m0\u001b[39m]\n\u001b[32m 2\u001b[39m md(f\"**Meilleur modèle :** {best_run[\u001b[33m'tags.model_name'\u001b[39m]} (F1 = {best_run[\u001b[33m'metrics.f1'\u001b[39m]:.3f})\")\n",
"\u001b[32mc:\\Users\\PC\\Desktop\\sprint5\\Churn-Prediction-avec-MLflow\\venv\\Lib\\site-packages\\pandas\\core\\frame.py\u001b[39m in \u001b[36m?\u001b[39m\u001b[34m(self, by, axis, ascending, inplace, kind, na_position, ignore_index, key)\u001b[39m\n\u001b[32m 7207\u001b[39m )\n\u001b[32m 7208\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m len(by):\n\u001b[32m 7209\u001b[39m \u001b[38;5;66;03m# len(by) == 1\u001b[39;00m\n\u001b[32m 7210\u001b[39m \n\u001b[32m-> \u001b[39m\u001b[32m7211\u001b[39m k = self._get_label_or_level_values(by[\u001b[32m0\u001b[39m], axis=axis)\n\u001b[32m 7212\u001b[39m \n\u001b[32m 7213\u001b[39m \u001b[38;5;66;03m# need to rewrap column in Series to apply key function\u001b[39;00m\n\u001b[32m 7214\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m key \u001b[38;5;28;01mis\u001b[39;00m \u001b[38;5;28;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
"\u001b[32mc:\\Users\\PC\\Desktop\\sprint5\\Churn-Prediction-avec-MLflow\\venv\\Lib\\site-packages\\pandas\\core\\generic.py\u001b[39m in \u001b[36m?\u001b[39m\u001b[34m(self, key, axis)\u001b[39m\n\u001b[32m 1910\u001b[39m values = self.xs(key, axis=other_axes[\u001b[32m0\u001b[39m])._values\n\u001b[32m 1911\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m self._is_level_reference(key, axis=axis):\n\u001b[32m 1912\u001b[39m values = self.axes[axis].get_level_values(key)._values\n\u001b[32m 1913\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1914\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m KeyError(key)\n\u001b[32m 1915\u001b[39m \n\u001b[32m 1916\u001b[39m \u001b[38;5;66;03m# Check for duplicates\u001b[39;00m\n\u001b[32m 1917\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m values.ndim > \u001b[32m1\u001b[39m:\n",
"\u001b[31mKeyError\u001b[39m: 'metrics.f1'"
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"**Meilleur modèle :** DummyModel (F1 = 0.500)"
],
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Expand All @@ -444,22 +466,10 @@
},
{
"cell_type": "code",
"execution_count": 66,
"execution_count": 173,
"id": "3f546c09",
"metadata": {},
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{
"ename": "NameError",
"evalue": "name 'best_run' is not defined",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mNameError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[66]\u001b[39m\u001b[32m, line 2\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# Chargement et test du modèle\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m2\u001b[39m model_uri = \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mruns:/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[43mbest_run\u001b[49m[\u001b[33m'\u001b[39m\u001b[33mrun_id\u001b[39m\u001b[33m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m/model\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 3\u001b[39m loaded_model = mlflow.sklearn.load_model(model_uri)\n",
"\u001b[31mNameError\u001b[39m: name 'best_run' is not defined"
]
}
],
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"source": [
"# Chargement et test du modèle\n",
"model_uri = f\"runs:/{best_run['run_id']}/model\"\n",
Expand All @@ -468,7 +478,7 @@
},
{
"cell_type": "code",
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"execution_count": 174,
"id": "638439a2",
"metadata": {},
"outputs": [],
Expand All @@ -491,13 +501,30 @@
"execution_count": null,
"id": "a5fa9d0a",
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"✅ Prédiction exemple :\n",
"[0 0 0 0 0]\n"
]
}
],
"source": [
"# Exemple d’un batch de test\n",
"X_test = joblib.load(\"data/X_test.pkl\")\n",
"print(\"✅ Prédiction exemple :\")\n",
"print(loaded_model.predict(X_test[:5]))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0983ddc2",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
Expand Down
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