{ "cells": [ { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import seaborn as sns\n", "from tqdm import tqdm_notebook as tqdm" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "from sklearn.decomposition import PCA\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import accuracy_score" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Данные:\n", "Будем работать с датасетом [FashionMNIST](https://github.com/zalandoresearch/fashion-mnist). " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import os\n", "import struct\n", "import numpy as np\n", "\n", "\n", "def load_mnist(path, which='train'):\n", "\n", " if which == 'train':\n", " labels_path = os.path.join(path, 'train-labels-idx1-ubyte')\n", " images_path = os.path.join(path, 'train-images-idx3-ubyte')\n", " elif which == 'test':\n", " labels_path = os.path.join(path, 't10k-labels-idx1-ubyte')\n", " images_path = os.path.join(path, 't10k-images-idx3-ubyte')\n", " else:\n", " raise AttributeError('`which` must be \"train\" or \"test\"')\n", "\n", " with open(labels_path, 'rb') as lbpath:\n", " magic, n = struct.unpack('>II', lbpath.read(8))\n", " labels = np.fromfile(lbpath, dtype=np.uint8)\n", "\n", " with open(images_path, 'rb') as imgpath:\n", " magic, n, rows, cols = struct.unpack('>IIII', imgpath.read(16))\n", " images = np.fromfile(imgpath, dtype=np.uint8).reshape(len(labels), 784)\n", "\n", " return images, labels" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "X_train, y_train = load_mnist(path='../data/', which='train')\n", "X_test, y_test = load_mnist(path='../data/', which='test')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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r3/R+M/uVmd1kZsf8bYxmtsHMNpnZprL8NzIDwHSgfgGYqnDTZGZzJX1d0gdT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\nu/Xb19CuknRL/eNbJL01530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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f = plt.figure(figsize=(10, 10))\n", "\n", "ax = plt.subplot(2, 2, 1)\n", "ax.imshow(X_train[0].reshape([28, 28]))\n", "\n", "ax = plt.subplot(2, 2, 2)\n", "i = np.random.randint(0, X_train.shape[0], 1)\n", "ax.imshow(X_train[i].reshape([28, 28]))\n", "\n", "ax = plt.subplot(2, 2, 3)\n", "i = np.random.randint(0, X_train.shape[0], 1)\n", "ax.imshow(X_train[i].reshape([28, 28]))\n", "\n", "ax = plt.subplot(2, 2, 4)\n", "i = np.random.randint(0, X_train.shape[0], 1)\n", "ax.imshow(X_train[i].reshape([28, 28]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Задание:\n", "Будем решать задачу классификации на 10 классов. Каждый класс соответствует одному из типов одежды. Исходная размерность признакового пространства: `784`, каждый пиксель является признаком. Будем снижать размерность признакового пространства с помощью метода главных компонент (`PCA`). Ваша задача оценить качество решенения задачи классификации по метрике `accuracy` в зависимости от числа главных компонент. Также оцените дисперсию функции качества в зависимости от числа главных компонент.\n", "\n", "Нарисуйте график зависимости функции качества и ее дисперсии от числа главных компонент." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.58389999999999997" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pca = PCA(n_components=3)\n", "used_indices = np.random.choice(\n", " np.arange(X_train.shape[0]), 10000, replace=False)\n", "X_train_lowdim = pca.fit_transform(X_train[used_indices].reshape([-1, 784]))\n", "lr = LogisticRegression()\n", "lr.fit(X_train_lowdim, y_train[used_indices])\n", "accuracy_score(y_test, lr.predict(pca.transform(X_test.reshape([-1, 784]))))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Используйте следующую сетку числа главных компонент: `[3, 5, 7, 12, 18, 25, 33, 40, 48, 55]`. Для ускорения сходимости можете семплировать подвыборки из `X_train`. " ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3076aa4bef0e4d9c8b32767c9aff6551" } }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "# Your code here\n", "\n", "#pca_steps = [3, 5, 7, 12, 18, 25, 33, 40, 48, 55]\n", "pca_steps = np.arange(2, 80, 3)\n", "n_repeat = 10\n", "\n", "results = []\n", "for pca_step in tqdm(pca_steps):\n", "\n", " result_step = []\n", " for i in range(n_repeat):\n", "\n", " pca = PCA(n_components=pca_step)\n", " used_indices = np.random.choice(\n", " np.arange(X_train.shape[0]), 10000, replace=False)\n", " X_train_reduced = pca.fit_transform(\n", " X_train[used_indices].reshape([-1, 784]))\n", "\n", " lr = LogisticRegression()\n", " lr.fit(X_train_reduced, y_train[used_indices])\n", "\n", " acc = accuracy_score(y_test, lr.predict(\n", " pca.transform(X_test.reshape([-1, 784]))))\n", " result_step.append(acc)\n", " results.append(result_step)\n", " \n", "results = np.array(results)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "plt.style.use('ggplot')\n", "sns.set(font_scale=2)\n", "\n", "\n", "def plot_results(results, steps, figsize=(10, 16)):\n", "\n", " means = results.mean(axis=1)\n", " stds = results.std(axis=1)\n", "\n", " f, ax = plt.subplots(2, 1, figsize=figsize)\n", " ax[0].plot(steps, means, '-', ms=10)\n", " ax[0].fill_between(steps, means - stds, means + stds, alpha=0.2)\n", "\n", " ax[0].set_xlabel('Number of PCA componens')\n", " ax[0].set_ylabel('Accuracy score')\n", "\n", " ax[1].plot(steps, stds**2)\n", " ax[1].set_xlabel('Number of PCA componens')\n", " ax[1].set_ylabel('Variance score')\n", "\n", " plt.ticklabel_format(axis='y', style='sci', scilimits=(1, 3))\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": 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/Og2z1YGxt8fi8bG3wGq2otJs7cRKOx//NjyxPVqwLTyxPTyxPVqwLTy11x4d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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_results(results, pca_steps)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Вывод:\n", "Для получения столь же хорошего accuracy как на всех данных, мы можем снизить размерность данных до ~40 компонент. Дисперсия функции качества одинакого мала при снижении размерности до любого числа компонент > 5" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.1" }, "toc": { "nav_menu": {}, "number_sections": false, "sideBar": false, "skip_h1_title": false, "toc_cell": false, "toc_position": {}, "toc_section_display": "block", "toc_window_display": false }, "varInspector": { "cols": { "lenName": 16, "lenType": 16, "lenVar": 40 }, "kernels_config": { "python": { "delete_cmd_postfix": "", "delete_cmd_prefix": "del ", "library": "var_list.py", "varRefreshCmd": "print(var_dic_list())" }, "r": { "delete_cmd_postfix": ") ", "delete_cmd_prefix": "rm(", "library": "var_list.r", "varRefreshCmd": "cat(var_dic_list()) " } }, "oldHeight": 377.4, "position": { "height": "40px", "left": "1166px", "right": "20px", "top": "120px", "width": "353px" }, "types_to_exclude": [ "module", "function", "builtin_function_or_method", "instance", "_Feature" ], "varInspector_section_display": "none", "window_display": true } }, "nbformat": 4, "nbformat_minor": 2 }