From a4990be99025f31c0f7cf0a7c3013a0bbff82ffa Mon Sep 17 00:00:00 2001
From: Quentin Fortier <qpfortier@gmail.com>
Date: Fri, 15 Dec 2023 15:22:08 +0100
Subject: [PATCH] Add knn_iris.ipynb

---
 .../cours/knn/exemple/knn_iris.ipynb          | 51 +++++++++++++++++++
 1 file changed, 51 insertions(+)

diff --git a/files/dl/apprentissage/cours/knn/exemple/knn_iris.ipynb b/files/dl/apprentissage/cours/knn/exemple/knn_iris.ipynb
index 2c650ff7..782d1646 100644
--- a/files/dl/apprentissage/cours/knn/exemple/knn_iris.ipynb
+++ b/files/dl/apprentissage/cours/knn/exemple/knn_iris.ipynb
@@ -30,6 +30,46 @@
     "<center><img src=https://raw.githubusercontent.com/cpge-itc/bcpst2/main/files/5_iris/iris.png width=60%></center>"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[0 0 1 2 1 2 1 0 0 0 2 0 0 0 0 1 0 0 1 1 0 0 1 1 0 1 1 0 0 1 2 0 1 0 2 0 1\n",
+      " 0 0 0 2 1 2 1 1 0 2 2 0 2 0 2 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 2 1 1 2 0 1 1\n",
+      " 2]\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "array([2, 1, 0, 2, 0, 2, 0, 1, 1, 1, 2, 1, 1, 1, 1, 0, 1, 1, 0, 0, 2, 1,\n",
+       "       0, 0, 2, 0, 0, 1, 1, 0, 2, 1, 0, 2, 2, 1, 0, 1, 1, 1, 2, 0, 2, 0,\n",
+       "       0, 1, 2, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 2, 1, 0, 2, 1, 1, 1,\n",
+       "       1, 2, 0, 0, 2, 1, 0, 0, 1])"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.model_selection import train_test_split # pour séparer les données en train et test\n",
+    "\n",
+    "X_train, X_test, Y_train, Y_test = train_test_split(iris.data, iris.target, test_size=0.5, shuffle=True, random_state=0)\n",
+    "\n",
+    "from sklearn.cluster import KMeans\n",
+    "kmeans = KMeans(n_clusters=3, random_state=0).fit(X_train)\n",
+    "Y_pred = kmeans.predict(X_test)\n",
+    "print(Y_pred)\n",
+    "Y_test"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -183,6 +223,17 @@
     "plt.show()\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn.model_selection import train_test_split # pour séparer les données en train et test\n",
+    "\n",
+    "X_train, X_test, Y_train, Y_test = train_test_split(iris.data, iris.target, test_size=0.5, shuffle=True, random_state=0)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},