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LinlyBoi
2023-05-15 19:48:38 +03:00
parent 701c3c6a87
commit 64fc005bfc
1 changed files with 0 additions and 37 deletions
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dwarves/Mining_HQ.ipynb
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@@ -1028,43 +1028,6 @@
"print(\"Number of mislabeled points out of a total %d points : %d\"\n",
" % (gammas_test.shape[0], (y_test != prediction).sum()))\n"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of mislabeled points out of a total 75 points : 4\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": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from sklearn.datasets import load_iris\n",
"X, y = load_iris(return_X_y=True)\n",
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5, random_state=0)\n",
"gnb = GaussianNB()\n",
"y_pred = gnb.fit(X_train, y_train).predict(X_test)\n",
"print(\"Number of mislabeled points out of a total %d points : %d\"\n",
" % (X_test.shape[0], (y_test != y_pred).sum()))\n",
"y_test"
]
}
],
"metadata": {