{ "cells": [ { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n", "/Users/ric7/anaconda3/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6\n", " return f(*args, **kwds)\n" ] } ], "source": [ "import keras\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from skimage import transform" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Данные:\n", "Будем работать с датасетом [FashionMNIST](https://github.com/zalandoresearch/fashion-mnist). " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz\n", "32768/29515 [=================================] - 0s 6us/step\n", "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz\n", "26427392/26421880 [==============================] - 11s 0us/step\n", "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz\n", "8192/5148 [===============================================] - 0s 0us/step\n", "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz\n", "4423680/4422102 [==============================] - 3s 1us/step\n" ] } ], "source": [ "from keras.datasets import fashion_mnist\n", "\n", "(X_train, y_train), (X_test, y_test) = fashion_mnist.load_data()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAFFhJREFUeJzt3WtwlFWaB/D/053OhdABwiUgRvGCCqMrOhFUphxHRgcta9FxtLQsF6uswdrVqZ1ZP2ixszXuh92yrFXXWndmNyorVo3OpUZXx6IcNa7ilSEiKwqLKERAIAlEkpCkk748+yHNTICc52369jae/6+KIumnT/qku/95u/u85xxRVRCRfyJhd4CIwsHwE3mK4SfyFMNP5CmGn8hTDD+Rpxh+Ik8x/ESeYviJPFVVzhurlhqtRX05b5LIKwkMYESHJZfrFhR+EVkK4FEAUQBPqOoD1vVrUY9FsqSQmyQiwzpty/m6eb/sF5EogH8HcDWA+QBuEZH5+f48IiqvQt7zLwTwmapuV9URAL8CsKw43SKiUisk/LMB7Brz/e7sZUcQkRUi0i4i7UkMF3BzRFRMhYR/vA8VjpkfrKqtqtqiqi0x1BRwc0RUTIWEfzeA5jHfnwxgT2HdIaJyKST86wHMFZHTRKQawM0AXixOt4io1PIe6lPVlIjcDeAPGB3qW6WqnxStZ0RUUgWN86vqGgBritQXIiojnt5L5CmGn8hTDD+Rpxh+Ik8x/ESeYviJPMXwE3mK4SfyFMNP5CmGn8hTDD+Rpxh+Ik8x/ESeKuvS3RQCCVjFWY9ZfOm4RKc2mvWvvneWs9bwzPsF3XbQ7yZVMWdNkyOF3Xahgh4XS4GP2WE88hN5iuEn8hTDT+Qphp/IUww/kacYfiJPMfxEnuI4/9ecRKNmXVMpsx5ZYO+9uuXOiXb7IXctNrDQbFs1lDHrsVfazXpBY/lB5xAE3K8Q+7haSN+kyoit/XAegUd+Ik8x/ESeYviJPMXwE3mK4SfyFMNP5CmGn8hTBY3zi0gHgH4AaQApVW0pRqeoeMwxYQSP8+/63mSzfuslb5n1d7pPd9a+qJlpttU6s4yq715i1s/6+ZfOWqpjp/3DA+bMB91vQaJTpriL6bTZNt3X5y4ex1T/Ypzk8x1V3V+En0NEZcSX/USeKjT8CuAVEflARFYUo0NEVB6FvuxfrKp7RGQGgFdF5P9Ude3YK2T/KKwAgFpMKPDmiKhYCjryq+qe7P9dAJ4HcMxMDVVtVdUWVW2JoaaQmyOiIso7/CJSLyLxw18DuArAx8XqGBGVViEv+5sAPC+jUx+rADyjqi8XpVdEVHJ5h19VtwM4v4h9oRLIJBIFtR+54JBZ/8Eke059bSTprL0Zsefrf/l6s1lP/4Xdty8ejjtrmQ8vNdtO/dgea2/4cK9Z33/ZbLPe/U33gHxTwHYGU1773FmTntwjzaE+Ik8x/ESeYviJPMXwE3mK4SfyFMNP5CnRIm33m4sGadRFsqRst+cNa5npgMf30E0Xm/Wrf/qGWZ9Xu8es92dqnbURLezs8se2ftusD2yf5KxFRgK2yA4op5vspbc1aR9Xp2xw/+51yzrNtvL4dGfto7ZHcahnV077f/PIT+Qphp/IUww/kacYfiJPMfxEnmL4iTzF8BN5iuP8lSBgO+iCBDy+535g//3//hR7ym6QqLGW9IBWm20PpusLuu3ulHtKbzLgHIMnttlTfg8Z5xAAQCRlP6ZXfudDZ+2GxvVm2wfPOM9ZW6dt6NMejvMTkRvDT+Qphp/IUww/kacYfiJPMfxEnmL4iTxVjF16qVBlPNfiaNsOzTDrBxommvV9KXsL76lR9/La8ciQ2XZOzN78uTvtHscHgGjMvTT4iEbNtv/4jd+b9cS8mFmPib3096XGOgg3bv4rs209tpv1XPHIT+Qphp/IUww/kacYfiJPMfxEnmL4iTzF8BN5KnCcX0RWAbgWQJeqnpu9rBHArwHMAdAB4CZV/ap03aRSmV5jb3NdK+4ttgGgWlJmfU9yirO2behss+2nffY5CEubPjHrSWMs31pnAAgepz8pZj/dE2qfB2Ddq4ub7HH8jWY1d7kc+Z8CsPSoy+4D0KaqcwG0Zb8nohNIYPhVdS2AnqMuXgZgdfbr1QCuK3K/iKjE8n3P36SqewEg+7/9+oyIKk7Jz+0XkRUAVgBALSaU+uaIKEf5Hvk7RWQWAGT/73JdUVVbVbVFVVtiqMnz5oio2PIN/4sAlme/Xg7gheJ0h4jKJTD8IvIsgPcAnC0iu0XkDgAPALhSRLYBuDL7PRGdQALf86vqLY4SF+AvloB1+yVqzz3XlHusPTrFPc4OAN+evMmsd6cbzPrBtP05zuTooLPWn6o12/YM2T/7nJq9Zn3D4BxnbXq1PU5v9RsAOkammfW5NfvM+oOd7vg01x49uHak1JLLnDVd957Zdiye4UfkKYafyFMMP5GnGH4iTzH8RJ5i+Ik8xaW7K0HA0t1SZT9M1lDfrjvmmW2vmGAvUf1uYrZZn17Vb9atabWzanrNtvGmhFkPGmZsrHJPV+5P15ltJ0SGzXrQ731htb3s+E9eu9BZi597wGzbEDOO2cex2zuP/ESeYviJPMXwE3mK4SfyFMNP5CmGn8hTDD+RpzjOXwEkVm3WMwl7vNsybdOIWd+ftpeYnhyxp7ZWByxxbW2FfWnjDrNtd8BY/Iah08x6POreAnx6xB6nb47ZY+2bEs1mfc3AmWb9jmtfc9aebb3SbFv98rvOmqj9eI3FIz+Rpxh+Ik8x/ESeYviJPMXwE3mK4SfyFMNP5KkTa5zfWOJaquzxaokG/J2L2PVMwpjfnbHHuoNo0h6LL8Sj//mYWd+VmmzW9yXtetAS12ljgvn7Q5PMtrURe3vw6VV9Zr0vY58nYOnP2MuKW+sUAMF9v3fqNmftud7vmm2LhUd+Ik8x/ESeYviJPMXwE3mK4SfyFMNP5CmGn8hTgeP8IrIKwLUAulT13Oxl9wP4IYDu7NVWquqaQjtTyPr0QWPlag+7hmpo2UKzvus6+zyCWy/4o7O2LxU3235obGMNAJOMOfEAUB+wvn1C3edf7Bmxtw8PGiu31uUHgBnGeQBptY97XybtvgUJOv9hd8rYU+Av7bUGJj+dV5eOkcuR/ykAS8e5/BFVXZD9V3Dwiai8AsOvqmsB9JShL0RURoW8579bRD4SkVUiUthrJCIqu3zD/wsAZwBYAGAvgIdcVxSRFSLSLiLtSdjvD4mofPIKv6p2qmpaVTMAHgfg/MRKVVtVtUVVW2KoybefRFRkeYVfRGaN+fZ6AB8XpztEVC65DPU9C+ByANNEZDeAnwG4XEQWAFAAHQDuLGEfiagERAP2hi+mBmnURbKkbLc3VtWsmWY9eVqTWe+Z594LfnCmvSn6gmu2mPXbm942693pBrMeE/f5D0H70M+MHTTrr/fON+sTq+zPcazzBC6s6zDbHsy473MAOKnqK7N+72c/cNaaJthj6U+cao9eJzVj1rcm7be48Yj7vJS3Bu01/5+fP91ZW6dt6NMe+wmZxTP8iDzF8BN5iuEn8hTDT+Qphp/IUww/kacqaunu4asvMusz/n67s7agYbfZdn6dPZyWyNhLf1vTSzcPzTbbDmbsLbi3jdjDkL0pe8grKu5hp64Re0rvQzvsZaLbFv6HWf/pnvEmfP5ZpM49lHwgPdFse8NEe2luwH7M7jxlrbN2enWX2falgVlmfU/AlN+mWK9ZnxPrdta+H//UbPs83EN9x4NHfiJPMfxEnmL4iTzF8BN5iuEn8hTDT+Qphp/IU+Ud5xd7ee5F/7zebL4k/omzNqj2FMqgcfygcVvLpCp7mebhpH03dyXtKbtBzqrZ56xd37DRbLv2sUVm/VuJH5n1z6/4L7PeNuTeyro7Zf/eN++4wqxv2Nls1i+es8NZOy/+pdk26NyKeDRh1q1p1gAwkHE/X99P2Oc/FAuP/ESeYviJPMXwE3mK4SfyFMNP5CmGn8hTDD+Rp8q6dHfdzGY947a/c9Zb7/o3s/0zPRc7a8219l6ip1bvN+tTo/Z2z5Z4xB7zPTtmj/m+NHCyWX/j4Dlm/ZvxDmctJvb23pdP+Mys3/6Te8x6qtZeJbpvjvv4kqq3n3sN5x8w6z8683WzXm387gfT9jh+0P0WtAV3EGsNhnjE3hb9oWuud9be63gKvUN7uXQ3Ebkx/ESeYviJPMXwE3mK4SfyFMNP5CmGn8hTgfP5RaQZwNMAZgLIAGhV1UdFpBHArwHMAdAB4CZVNfdMjiSBCZ3u8c2X+haYfTm9zr3W+f6kvT79Hw6dZ9ZPrrO3e7a2mj7TmE8PABsTk836y93fMOsn1dnr13cmJzlrB5L1ZttBY145ADz5yMNm/aFOe93/6xs3OGvnV9vj+Acz9rFpc8B+B/2ZWmctofb6Dr0B5wHEjecDACTVjlbU2OJ7csQ+h6DvvKnOWroz9yU6cjnypwDco6rzAFwM4C4RmQ/gPgBtqjoXQFv2eyI6QQSGX1X3quqG7Nf9ALYAmA1gGYDV2autBnBdqTpJRMV3XO/5RWQOgAsArAPQpKp7gdE/EABmFLtzRFQ6OYdfRCYC+B2AH6tq0CZqY9utEJF2EWlPDQ/k00ciKoGcwi8iMYwG/5eq+lz24k4RmZWtzwIw7s6Hqtqqqi2q2lJVY3/4RETlExh+EREATwLYoqpjP/p9EcDy7NfLAbxQ/O4RUankMi6wGMBtADaJyOF1oFcCeADAb0TkDgA7AdwY9IOiIxnEdw076xm1ZyK+vt89tbWptt9suyC+y6xvHbSHjTYNneSsbag6xWxbF3Vv7w0Ak6rtKcH1Ve77DACmxdy/+2k19lbU1rRXAFifsH+3v57+hlnfmXIvif77gbPMtpsH3fc5AEwJWDJ9U5+7/WDK3jZ9OG1HI5Gyh44n1diP6UWNXzhrW2FvD959vjFN+h2z6RECw6+qbwNwpXJJ7jdFRJWEZ/gReYrhJ/IUw0/kKYafyFMMP5GnGH4iT5V3i+5DQ4i8+aGz/NtXFpvN/2HZb521NwOWt35pnz0u2zdiT22dPsF9anKDMc4OAI0x+7TmoC2+awO2e/4q5T5zcjhiT11NO0dxR+0bdk8XBoB3MnPNejLj3qJ72KgBwedH9IxMM+sn1fU6a/0p93RfAOjobzTr+3vtbbQTE+xovZ0+w1lbOtO9FT0A1HW5H7OI/VQ58rq5X5WIvk4YfiJPMfxEnmL4iTzF8BN5iuEn8hTDT+Spsm7R3SCNukjynwXce6t7i+7T/2ar2Xbh5B1mfUOfPW99pzHumwxYYjoWcS/TDAATYiNmvTZgvLs66p6TH4H9+GYCxvnro3bfgtYaaKhyz2uPR+057xFjG+tcRI3f/Y+9cwr62fGA3zul9nPikkmfO2urdlxqtp10jXtb9XXahj7t4RbdROTG8BN5iuEn8hTDT+Qphp/IUww/kacYfiJPlX+cP3qV+woZew35QgzcsMisL1q53q7H3eOy51R3mm1jsMerawPGs+sj9rBtwngMg/66vz3UbNbTAT/h9a/mmfWkMd7dOdhgto0Z5y/kwtoHYigVsEX3kD3fPxqxc5N4w15rYOpm97kbNWvs56KF4/xEFIjhJ/IUw0/kKYafyFMMP5GnGH4iTzH8RJ4KHOcXkWYATwOYCSADoFVVHxWR+wH8EEB39qorVXWN9bMKnc9fqeQie0+AoZl1Zr3mgD03vP9Uu33D5+59ASLD9kLumf/dYtbpxHI84/y5bNqRAnCPqm4QkTiAD0Tk1WztEVX9l3w7SkThCQy/qu4FsDf7db+IbAEwu9QdI6LSOq73/CIyB8AFANZlL7pbRD4SkVUiMsXRZoWItItIexL2y1siKp+cwy8iEwH8DsCPVbUPwC8AnAFgAUZfGTw0XjtVbVXVFlVticHeD4+Iyien8ItIDKPB/6WqPgcAqtqpqmlVzQB4HMDC0nWTiIotMPwiIgCeBLBFVR8ec/msMVe7HsDHxe8eEZVKLp/2LwZwG4BNIrIxe9lKALeIyAIACqADwJ0l6eEJQNdvMuv25NBgDe/m37awxa/p6yyXT/vfBsZd3N0c0yeiysYz/Ig8xfATeYrhJ/IUw0/kKYafyFMMP5GnGH4iTzH8RJ5i+Ik8xfATeYrhJ/IUw0/kKYafyFMMP5GnyrpFt4h0A/hizEXTAOwvWweOT6X2rVL7BbBv+Spm305V1em5XLGs4T/mxkXaVbUltA4YKrVvldovgH3LV1h948t+Ik8x/ESeCjv8rSHfvqVS+1ap/QLYt3yF0rdQ3/MTUXjCPvITUUhCCb+ILBWRrSLymYjcF0YfXESkQ0Q2ichGEWkPuS+rRKRLRD4ec1mjiLwqItuy/4+7TVpIfbtfRL7M3ncbReSakPrWLCL/IyJbROQTEfnb7OWh3ndGv0K538r+sl9EogA+BXAlgN0A1gO4RVU3l7UjDiLSAaBFVUMfExaRywAcAvC0qp6bvexBAD2q+kD2D+cUVb23Qvp2P4BDYe/cnN1QZtbYnaUBXAfgdoR43xn9ugkh3G9hHPkXAvhMVber6giAXwFYFkI/Kp6qrgXQc9TFywCszn69GqNPnrJz9K0iqOpeVd2Q/bofwOGdpUO974x+hSKM8M8GsGvM97tRWVt+K4BXROQDEVkRdmfG0ZTdNv3w9ukzQu7P0QJ3bi6no3aWrpj7Lp8dr4stjPCPt/tPJQ05LFbVCwFcDeCu7Mtbyk1OOzeXyzg7S1eEfHe8LrYwwr8bQPOY708GsCeEfoxLVfdk/+8C8Dwqb/fhzsObpGb/7wq5P39SSTs3j7ezNCrgvqukHa/DCP96AHNF5DQRqQZwM4AXQ+jHMUSkPvtBDESkHsBVqLzdh18EsDz79XIAL4TYlyNUys7Nrp2lEfJ9V2k7Xodykk92KONfAUQBrFLVfyp7J8YhIqdj9GgPjG5i+kyYfRORZwFcjtFZX50AfgbgvwH8BsApAHYCuFFVy/7Bm6Nvl2P0peufdm4+/B67zH37FoC3AGzCnzcqXonR99eh3XdGv25BCPcbz/Aj8hTP8CPyFMNP5CmGn8hTDD+Rpxh+Ik8x/ESeYviJPMXwE3nq/wHG6/IGFn5KEQAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.imshow(X_train[0].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": 8, "metadata": {}, "outputs": [], "source": [ "from sklearn.decomposition import PCA\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import accuracy_score" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.5787" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pca = PCA(n_components=3)\n", "used_indices = np.random.choice(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": [], "source": [ "pca = PCA(n_components=3)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Классифицируем данные с помощью лог. регрессии для каждого из значений из списка заданных параметров. Результаты запишем в массив." ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "components_options = [3, 5, 7, 12, 18, 25, 33, 40, 48, 55]\n", "\n", "results = []\n", "\n", "for n_comps in components_options:\n", " pca = PCA(n_components=n_comps)\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", " results.append(acc)\n", " \n", "results = np.array(results)\n", "components_options = np.array(components_options)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Настроим параметры для построения графиков" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [], "source": [ "plt.rcParams['font.family'] = 'serif'\n", "plt.rcParams['font.serif'] = 'CMU Serif'\n", "plt.rcParams['lines.linewidth'] = 2\n", "plt.rcParams['lines.markersize'] = 12\n", "plt.rcParams['xtick.labelsize'] = 24\n", "plt.rcParams['ytick.labelsize'] = 24\n", "plt.rcParams['legend.fontsize'] = 24\n", "plt.rcParams['axes.titlesize'] = 36\n", "plt.rcParams['axes.labelsize'] = 24" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,7))\n", "plt.plot(components_options, results)\n", "plt.grid()\n", "plt.xlabel(\"Number of components\")\n", "plt.ylabel(\"Accuracy metric\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Усложним вычисление: для каждого теста будем прогонять 10 экспериментов. " ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "results = []\n", "variance_of_accuracy = []\n", "n_tests = 10\n", "for n_comps in components_options:\n", " scores = [] \n", " for i in range(n_tests):\n", " pca = PCA(n_components=n_comps)\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", " lr.fit(X_train_reduced, y_train[used_indices])\n", " scores.append(accuracy_score(\n", " y_test, lr.predict(pca.transform(X_test.reshape([-1, 784])))))\n", " results.append(np.mean(scores))\n", " variance_of_accuracy.append(np.var(scores))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Используя новые данные построим график дисперсии" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,7))\n", "plt.plot(components_options, variance_of_accuracy)\n", "plt.grid()\n", "plt.xlabel(\"Number of components\")\n", "plt.ylabel(\"Variance of accuracy\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "так как дисперсия достаточно низкая при большом количестве главных компонент, новый график точности не должен сильно отличаться от предыдущего (без усреднений)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,7))\n", "plt.plot(components_options, results)\n", "plt.grid()\n", "plt.xlabel(\"Number of components\")\n", "plt.ylabel(\"Accuracy metric\")\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "так и есть." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Вывод: оптимальное количество главных компонент 35+" ] } ], "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": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }