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add: TP1/2

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Arthur Danjou
2025-03-24 16:07:17 +01:00
parent f41866ea2f
commit e1ec07b5c7
2 changed files with 47 additions and 56 deletions
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28
M1/Numerical Methods/TP2.ipynb
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@@ -17,13 +17,12 @@
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-03-24T13:10:01.794956Z",
"start_time": "2025-03-24T13:09:58.777694Z"
"end_time": "2025-03-24T14:45:40.568860Z",
"start_time": "2025-03-24T14:45:37.895550Z"
}
},
"cell_type": "code",
"source": [
"\n",
"import numpy as np\n",
"from sklearn.neural_network import MLPClassifier\n",
"from sklearn.datasets import make_classification\n",
@@ -42,7 +41,7 @@
" y_pred = model.predict(X_test)\n",
" accuracies.append(accuracy_score(y_test, y_pred))\n",
"\n",
"print(f'Accuracy: {np.mean(accuracies) * 100:.0f}%')\n",
"print(f'Mean Accuracy: {np.mean(accuracies) * 100:.0f}%')\n",
"print(f\"Max accuracy: {np.max(accuracies) * 100:.0f}%\")\n",
"print(f\"Min accuracy: {np.min(accuracies) * 100:.0f}%\")"
],
@@ -52,21 +51,26 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Accuracy: 93%\n",
"Max accuracy: 100%\n",
"Min accuracy: 80%\n"
"Mean Accuracy: 92%\n",
"Max accuracy: 96%\n",
"Min accuracy: 86%\n"
]
}
],
"execution_count": 21
"execution_count": 28
},
{
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2025-03-24T14:37:53.507776Z",
"start_time": "2025-03-24T14:37:53.505376Z"
}
},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": "",
"id": "96b6d46883ed5570"
"id": "96b6d46883ed5570",
"outputs": [],
"execution_count": null
}
],
"metadata": {