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predict.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "47153112-da26-4dbd-a32a-1abdd8bda4fa",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2949/2949 [==============================] - 2s 498us/step\n"
+     ]
+    }
+   ],
+   "source": [
+    "import tensorflow as tf\n",
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import sklearn\n",
+    "import sklearn.model_selection\n",
+    "from tensorflow.keras.models import load_model\n",
+    "from sklearn.metrics import accuracy_score, precision_score, f1_score\n",
+    "\n",
+    "feature_cols = ['year', 'mileage', 'vol_engine']\n",
+    "\n",
+    "model = load_model('model.h5')\n",
+    "test_data = pd.read_csv('test.csv')\n",
+    "\n",
+    "predictions = model.predict(test_data[feature_cols])\n",
+    "predicted_prices = [p[0] for p in predictions]\n",
+    "\n",
+    "\n",
+    "results = pd.DataFrame({'id': test_data['id'], 'year': test_data['year'], 'mileage': test_data['mileage'], 'vol_engine': test_data['vol_engine'], 'predicted_price': predicted_prices})\n",
+    "results.to_csv('predictions.csv', index=False)\n",
+    "\n",
+    "y_true = test_data['price']\n",
+    "y_pred = y_pred = [round(p[0]) for p in predictions]\n",
+    "\n",
+    "accuracy = accuracy_score(y_true, y_pred)\n",
+    "precision = precision_score(y_true, y_pred, average='micro')\n",
+    "f1 = f1_score(y_true, y_pred, average='micro')\n",
+    "\n",
+    "with open('metrics.txt', 'w') as f:\n",
+    "    f.write(f\"Accuracy: {accuracy:.4f}\\n\")\n",
+    "    f.write(f\"Micro-average Precision: {precision:.4f}\\n\")\n",
+    "    f.write(f\"Micro-average F1-score: {f1:.4f}\\n\")\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "bca76252-c90d-4343-8ff8-a665cd32cf26",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}