diff --git a/Lab_5/lab5.ipynb b/Lab_5/lab5.ipynb new file mode 100644 index 0000000..8368036 --- /dev/null +++ b/Lab_5/lab5.ipynb @@ -0,0 +1,320 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "e7893b9e", + "metadata": {}, + "source": [ + "# Лабораторная работа: Методы искусственного интеллекта\n", + "## Задача кластеризации продуктов с использованием cuML\n", + "### Вариант: Продукты\n", + "В данной работе используется библиотека cuML для GPU-ускоренного анализа данных. Цель: провести кластеризацию продуктов на основе их характеристик." + ] + }, + { + "cell_type": "markdown", + "id": "e3834005", + "metadata": {}, + "source": [ + "### Загрузка и исследование данных" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "5530d138", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 162313 entries, 0 to 162312\n", + "Data columns (total 5 columns):\n", + " # Column Non-Null Count Dtype\n", + "--- ------ -------------- -----\n", + " 0 category 162313 non-null object\n", + " 1 sub_category 162313 non-null object\n", + " 2 href 162313 non-null object\n", + " 3 items 162280 non-null object\n", + " 4 price 162282 non-null float64\n", + "dtypes: float64(1), object(4)\n", + "memory usage: 28.9+ MB\n", + "None\n", + " category sub_category \\\n", + "0 Groceries Fruits & Vegetables \n", + "1 Groceries Fruits & Vegetables \n", + "2 Groceries Fruits & Vegetables \n", + "3 Groceries Fruits & Vegetables \n", + "4 Groceries Fruits & Vegetables \n", + "\n", + " href \\\n", + "0 https://www.jiomart.com/c/groceries/fruits-veg... \n", + "1 https://www.jiomart.com/c/groceries/fruits-veg... \n", + "2 https://www.jiomart.com/c/groceries/fruits-veg... \n", + "3 https://www.jiomart.com/c/groceries/fruits-veg... \n", + "4 https://www.jiomart.com/c/groceries/fruits-veg... \n", + "\n", + " items price \n", + "0 Fresh Dates (Pack) (Approx 450 g - 500 g) 109.0 \n", + "1 Tender Coconut Cling Wrapped (1 pc) (Approx 90... 49.0 \n", + "2 Mosambi 1 kg 69.0 \n", + "3 Orange Imported 1 kg 125.0 \n", + "4 Banana Robusta 6 pcs (Box) (Approx 800 g - 110... 44.0 \n" + ] + } + ], + "source": [ + "import cudf\n", + "import cuml\n", + "from cuml.preprocessing import LabelEncoder\n", + "from cuml.decomposition import PCA\n", + "from cuml.cluster import KMeans\n", + "import cupy as cp\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Загрузка данных\n", + "df = cudf.read_csv('/mnt/c/3curse/mii/AIM-PIbd-31-Medvedkov-A-D/data/jio_mart_items.csv')\n", + "print(df.info())\n", + "print(df.head())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b5ea4ef3", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "49112908", + "metadata": {}, + "source": [ + "### Предварительная обработка данных" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "1e3ef9fa", + "metadata": {}, + "outputs": [], + "source": [ + "# Обработка пропущенных значений\n", + "df = df.dropna()\n", + "\n", + "# Кодирование категориального признака 'items'\n", + "label_encoder = LabelEncoder()\n", + "df['items_encoded'] = label_encoder.fit_transform(df['items'])\n", + "\n", + "# Нормализация числовых признаков\n", + "numeric_features = ['items_encoded', 'price']\n", + "df_scaled = df[numeric_features].astype('float32')\n", + "\n", + "# Преобразование данных в формат cupy\n", + "X = cp.asarray(df_scaled.values)" + ] + }, + { + "cell_type": "markdown", + "id": "ff5f1f8f", + "metadata": {}, + "source": [ + "### Понижение размерности и визуализация данных" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "e15c80bb", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Применение PCA для понижения размерности\n", + "pca = PCA(n_components=2)\n", + "reduced_data = pca.fit_transform(X)\n", + "\n", + "# Преобразуем данные из cupy в numpy\n", + "reduced_data_np = reduced_data.get()\n", + "\n", + "# Визуализация данных\n", + "plt.scatter(reduced_data_np[:, 0], reduced_data_np[:, 1])\n", + "plt.title('Визуализация данных после PCA')\n", + "plt.xlabel('PC1')\n", + "plt.ylabel('PC2')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "f2eef505", + "metadata": {}, + "source": [ + "### Выбор оптимального количества кластеров" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "f72195d2", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Оценка числа кластеров: 100%|█████████████████████████████████████████████████████████████| 9/9 [01:08<00:00, 7.67s/it]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Оценка инерции и коэффициента силуэта\n", + "from cuml.metrics.cluster import silhouette_score\n", + "from tqdm import tqdm # Импорт библиотеки для отображения прогресса\n", + "\n", + "# Оценка инерции и коэффициента силуэта\n", + "inertia = []\n", + "silhouette_scores = []\n", + "k_range = range(2, 11)\n", + "\n", + "# tqdm для отображения прогресса\n", + "for k in tqdm(k_range, desc=\"Оценка числа кластеров\"):\n", + " kmeans = KMeans(n_clusters=k, random_state=42)\n", + " kmeans.fit(reduced_data)\n", + " inertia.append(kmeans.inertia_)\n", + " silhouette_scores.append(silhouette_score(reduced_data, kmeans.labels_))\n", + "\n", + "# Построение графиков\n", + "plt.figure(figsize=(14, 5))\n", + "\n", + "# График инерции\n", + "plt.subplot(1, 2, 1)\n", + "plt.plot(k_range, inertia, marker='o')\n", + "plt.title('Критерий инерции')\n", + "plt.xlabel('Число кластеров')\n", + "plt.ylabel('Инерция')\n", + "\n", + "# График коэффициента силуэта\n", + "plt.subplot(1, 2, 2)\n", + "plt.plot(k_range, silhouette_scores, marker='o')\n", + "plt.title('Коэффициент силуэта')\n", + "plt.xlabel('Число кластеров')\n", + "plt.ylabel('Силуэт')\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "180e85ac", + "metadata": {}, + "source": [ + "### Кластерный анализ" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "dd573024", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Кластеризация с использованием KMeans\n", + "optimal_k = 4 # Выбираем на основе графиков\n", + "kmeans = KMeans(n_clusters=optimal_k, random_state=42)\n", + "labels = kmeans.fit_predict(reduced_data)\n", + "\n", + "# Преобразуем данные из cupy в numpy\n", + "reduced_data_np = reduced_data.get()\n", + "labels_np = labels.get()\n", + "\n", + "# Визуализация кластеров\n", + "plt.scatter(reduced_data_np[:, 0], reduced_data_np[:, 1], c=labels_np, cmap='viridis')\n", + "plt.title('Кластеры (KMeans)')\n", + "plt.xlabel('PC1')\n", + "plt.ylabel('PC2')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "407d268e", + "metadata": {}, + "source": [ + "### Оценка качества кластеризации" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "d00795e2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Силуэт для кластеризации: 0.58\n" + ] + } + ], + "source": [ + "# Оценка коэффициента силуэта\n", + "silhouette = silhouette_score(reduced_data, labels)\n", + "print(f'Силуэт для кластеризации: {silhouette:.2f}')" + ] + }, + { + "cell_type": "markdown", + "id": "7b4aa1da", + "metadata": {}, + "source": [ + "Получился вплоне неплохой силуэт кластеризации, кластеры хорошо различимы, хоть и имеют пересечение." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}