Obisidian vault auto-backup: 29-09-2025 16:59:16 on . 1 files edited

ISEN/IA/CIPA4/TP/TP2/tp2_IA.ipynb

@@ -2500,7 +2500,45 @@
    "id": "3fba9380",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "print(\"=== Création d'un vecteur multi-label ===\\n\")\n",
+    "\n",
+    "# a. Stocker True si les labels sont supérieurs à 7, False sinon\n",
+    "labels_sup_7 = (Y_train > 7)\n",
+    "print(f\"Type: {type(labels_sup_7)}\")\n",
+    "print(f\"Forme: {labels_sup_7.shape}\")\n",
+    "print(f\"Exemples (premiers 20): {labels_sup_7.iloc[:20].values}\")\n",
+    "\n",
+    "# Statistiques\n",
+    "nb_sup_7 = np.sum(labels_sup_7)\n",
+    "print(f\"Nombre de labels > 7: {nb_sup_7}\")\n",
+    "print(f\"Pourcentage: {(nb_sup_7 / len(Y_train) * 100):.2f}%\")\n",
+    "\n",
+    "# b. Stocker True si les labels sont impairs, False sinon\n",
+    "labels_impairs = (Y_train % 2 == 1)\n",
+    "print(f\"Type: {type(labels_impairs)}\")\n",
+    "print(f\"Forme: {labels_impairs.shape}\")\n",
+    "print(f\"Exemples (premiers 20): {labels_impairs.iloc[:20].values}\")\n",
+    "\n",
+    "# Statistiques\n",
+    "nb_impairs = np.sum(labels_impairs)\n",
+    "print(f\"Nombre de labels impairs: {nb_impairs}\")\n",
+    "print(f\"Pourcentage: {(nb_impairs / len(Y_train) * 100):.2f}%\")\n",
+    "\n",
+    "# c. Concaténer les deux vecteurs avec numpy.c_\n",
+    "vecteur_multilabel = np.c_[labels_sup_7, labels_impairs]\n",
+    "print(f\"Type: {type(vecteur_multilabel)}\")\n",
+    "print(f\"Forme: {vecteur_multilabel.shape}\")\n",
+    "print(f\"Premières 20 lignes:\")\n",
+    "print(\"[Sup_7, Impair]\")\n",
+    "for i in range(20):\n",
+    "    sup7 = vecteur_multilabel[i, 0]\n",
+    "    impair = vecteur_multilabel[i, 1]\n",
+    "    label_original = Y_train.iloc[i]\n",
+    "    print(f\"[{sup7:5}, {impair:5}] - Label original: {label_original}\")\n"
+   ]
   }
  ],
  "metadata": {