diff --git a/predict.ipynb b/predict.ipynb new file mode 100644 index 0000000..5e0532d --- /dev/null +++ b/predict.ipynb @@ -0,0 +1,84 @@ +{ + "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 +}