09. k-NEAREST NEIGHBOUR ALGORITHM (USING API).ipynb

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    "import numpy as np\n",
    "from sklearn.datasets import load_iris\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.neighbors import KNeighborsClassifier"
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    "dataset = load_iris()\n",
    "#print(dataset)\n",
    "X_train, X_test, y_train, y_test = train_test_split(dataset[\"data\"],\n",
    "                                                    dataset[\"target\"],\n",
    "                                                    random_state=0)"
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       "KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "                     metric_params=None, n_jobs=None, n_neighbors=1, p=2,\n",
       "                     weights='uniform')"
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    "kn = KNeighborsClassifier(n_neighbors=1)\n",
    "kn.fit(X_train, y_train)"
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    "prediction = kn.predict(X_test)\n",
    "confusion_matrix(y_test, prediction)"
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