{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "Решить задачу: кластеризации/классификации \n", "\n", "На выборке: MNIST \n", "\n", "С использованием моделей: PCA + K-means \n", "\n", "Со структурным параметром: количество главных компонент в PCA \n", "\n", "\n", "С критериями качества: однородность кластеров, Accuracy" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "C:\\Users\\Poly\\Anaconda3\\lib\\site-packages\\h5py\\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n", " from ._conv import register_converters as _register_converters\n", "Using TensorFlow backend.\n" ] } ], "source": [ "import numpy as np\n", "from sklearn import datasets, metrics\n", "from keras.datasets import mnist\n", "from sklearn.cluster import KMeans\n", "from sklearn.decomposition import PCA" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Загружаем данные" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "(x_train,y_train),(x_test,y_test)=mnist.load_data()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Приводим данные к двумерному виду" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "data_test=x_test.reshape((len(x_test),-1))\n", "data_train=x_train.reshape((len(x_train),-1))" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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255, 255, 255, 255, 255, 255, 255, 255, 254,\n", " 252, 247, 113, 188, 254, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 254, 52, 37, 226, 254, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 190, 40, 107, 254, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 254, 223, 0, 133, 254, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 253, 104, 60, 197, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 153, 15,\n", " 166, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 253,\n", " 128, 0, 185, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 51, 32, 185, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 252, 39, 31, 38, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 254, 225, 72, 0, 0, 217, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 254, 150, 0, 0, 0, 253, 253,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 254, 252, 98, 0, 0, 0,\n", " 42, 254, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 253, 127, 104, 0,\n", " 0, 0, 0, 38, 255, 255, 255, 255, 255, 255, 255, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 137, 28, 59,\n", " 0, 0, 0, 0, 0, 0, 94, 252, 245, 254, 254, 255, 255,\n", " 255, 255, 255, 255, 255, 255, 255, 254, 254, 253, 253, 254, 62,\n", " 0, 0, 0, 0], dtype=uint8)), mean=array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 2.10000000e-03, 7.83333333e-03, 3.60000000e-03, 1.50000000e-04,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 2.66666667e-04, 9.16666667e-04, 9.28333333e-03, 2.42833333e-02,\n", " 4.37166667e-02, 6.41000000e-02, 1.20133333e-01, 1.60733333e-01,\n", " 1.74183333e-01, 1.77433333e-01, 1.89316667e-01, 1.74150000e-01,\n", " 1.86933333e-01, 1.53650000e-01, 1.00116667e-01, 7.12333333e-02,\n", " 5.38166667e-02, 2.13666667e-02, 1.00833333e-02, 3.53333333e-03,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 1.06666667e-03, 7.00000000e-04,\n", " 6.95000000e-03, 5.48333333e-03, 4.71000000e-02, 1.38400000e-01,\n", " 2.64183333e-01, 5.06616667e-01, 8.66800000e-01, 1.29008333e+00,\n", " 1.87035000e+00, 2.52995000e+00, 3.20161667e+00, 3.62555000e+00,\n", " 3.72198333e+00, 3.39255000e+00, 2.80293333e+00, 2.04438333e+00,\n", " 1.20211667e+00, 6.33450000e-01, 2.96166667e-01, 9.39833333e-02,\n", " 3.52166667e-02, 8.63333333e-03, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 3.23333333e-03, 5.85000000e-03,\n", " 1.20166667e-02, 6.97666667e-02, 2.12083333e-01, 5.46100000e-01,\n", " 1.15441667e+00, 2.21590000e+00, 3.63963333e+00, 5.43800000e+00,\n", " 7.40705000e+00, 9.69673333e+00, 1.18830833e+01, 1.32373667e+01,\n", " 1.31246167e+01, 1.18135167e+01, 9.54366667e+00, 6.86305000e+00,\n", " 4.19365000e+00, 2.27463333e+00, 1.06103333e+00, 4.13066667e-01,\n", " 1.62083333e-01, 2.77666667e-02, 2.80000000e-03, 0.00000000e+00,\n", " 0.00000000e+00, 6.33333333e-04, 5.21666667e-03, 1.43500000e-02,\n", " 8.08833333e-02, 4.10216667e-01, 1.04323333e+00, 2.41928333e+00,\n", " 4.77575000e+00, 8.39441667e+00, 1.33102667e+01, 1.94773000e+01,\n", " 2.70366833e+01, 3.52121667e+01, 4.18408000e+01, 4.52526000e+01,\n", " 4.43388333e+01, 3.91414500e+01, 3.13282167e+01, 2.29239333e+01,\n", " 1.48310167e+01, 8.66140000e+00, 4.54796667e+00, 2.13701667e+00,\n", " 8.62900000e-01, 2.07750000e-01, 2.96500000e-02, 2.03333333e-03,\n", " 0.00000000e+00, 0.00000000e+00, 1.03166667e-02, 6.33500000e-02,\n", " 3.95466667e-01, 1.46340000e+00, 3.58778333e+00, 7.22781667e+00,\n", " 1.30171167e+01, 2.12179167e+01, 3.15004000e+01, 4.42063667e+01,\n", " 5.89038500e+01, 7.38041500e+01, 8.51027333e+01, 9.05997833e+01,\n", " 8.89239333e+01, 8.01812500e+01, 6.59428167e+01, 4.97938333e+01,\n", " 3.43498333e+01, 2.15100000e+01, 1.23903167e+01, 6.63911667e+00,\n", " 2.99271667e+00, 8.43666667e-01, 1.41633333e-01, 4.70000000e-03,\n", " 0.00000000e+00, 1.83333333e-04, 2.75000000e-02, 2.21433333e-01,\n", " 1.11951667e+00, 3.28990000e+00, 7.43646667e+00, 1.42544333e+01,\n", " 2.41377500e+01, 3.72885167e+01, 5.31154000e+01, 7.09128167e+01,\n", " 8.92784667e+01, 1.06232967e+02, 1.18506117e+02, 1.24098150e+02,\n", " 1.21711333e+02, 1.12033333e+02, 9.61081167e+01, 7.51653667e+01,\n", " 5.40371167e+01, 3.53124833e+01, 2.09919000e+01, 1.14424333e+01,\n", " 5.38776667e+00, 1.85558333e+00, 3.72700000e-01, 3.03000000e-02,\n", " 7.83333333e-04, 1.97333333e-02, 1.07666667e-01, 5.95650000e-01,\n", " 2.31240000e+00, 5.92876667e+00, 1.24360500e+01, 2.24518000e+01,\n", " 3.62947833e+01, 5.38984167e+01, 7.37647167e+01, 9.41030833e+01,\n", " 1.11579483e+02, 1.24999917e+02, 1.32759117e+02, 1.35398700e+02,\n", " 1.33338650e+02, 1.26677533e+02, 1.13546667e+02, 9.37442667e+01,\n", " 6.97779333e+01, 4.68328833e+01, 2.81439167e+01, 1.52010500e+01,\n", " 7.03366667e+00, 2.58303333e+00, 5.13100000e-01, 3.18833333e-02,\n", " 4.06666667e-03, 5.08166667e-02, 3.29366667e-01, 1.31735000e+00,\n", " 3.74813333e+00, 8.48346667e+00, 1.68181833e+01, 2.95974000e+01,\n", " 4.69301500e+01, 6.81070000e+01, 9.02913833e+01, 1.08475717e+02,\n", " 1.19435417e+02, 1.23393850e+02, 1.23038050e+02, 1.22340650e+02,\n", " 1.22730050e+02, 1.22144100e+02, 1.16260933e+02, 1.00610600e+02,\n", " 7.73180333e+01, 5.28976000e+01, 3.18106167e+01, 1.63576667e+01,\n", " 7.18566667e+00, 2.60661667e+00, 4.81583333e-01, 2.71833333e-02,\n", " 4.86666667e-03, 7.94666667e-02, 5.12016667e-01, 1.71938333e+00,\n", " 4.44581667e+00, 9.80663333e+00, 1.95264833e+01, 3.45048167e+01,\n", " 5.47009000e+01, 7.81380333e+01, 9.90387000e+01, 1.10600467e+02,\n", " 1.10787550e+02, 1.04553617e+02, 9.90472000e+01, 9.93883833e+01,\n", " 1.04333217e+02, 1.10882067e+02, 1.11078267e+02, 9.91469167e+01,\n", " 7.70405500e+01, 5.27057667e+01, 3.14484167e+01, 1.53927167e+01,\n", " 5.96113333e+00, 1.89796667e+00, 3.51833333e-01, 2.82166667e-02,\n", " 6.66666667e-03, 9.85666667e-02, 5.23033333e-01, 1.67458333e+00,\n", " 4.28908333e+00, 9.87643333e+00, 2.05393167e+01, 3.71890333e+01,\n", " 5.97151167e+01, 8.33987333e+01, 1.00225900e+02, 1.03168817e+02,\n", " 9.38921333e+01, 8.29528167e+01, 7.94228333e+01, 8.45250167e+01,\n", " 9.38685833e+01, 1.04427533e+02, 1.06281183e+02, 9.42218667e+01,\n", " 7.18490667e+01, 4.83172500e+01, 2.84781833e+01, 1.34981667e+01,\n", " 4.60050000e+00, 1.15010000e+00, 2.21833333e-01, 1.87333333e-02,\n", " 5.93333333e-03, 7.64000000e-02, 4.20883333e-01, 1.28036667e+00,\n", " 3.64608333e+00, 9.55390000e+00, 2.11332333e+01, 3.98545167e+01,\n", " 6.40892167e+01, 8.72096667e+01, 9.87805833e+01, 9.48668500e+01,\n", " 8.16835333e+01, 7.33427667e+01, 7.61450667e+01, 8.54255500e+01,\n", " 9.72928000e+01, 1.07482583e+02, 1.05509433e+02, 8.90295000e+01,\n", " 6.49443500e+01, 4.24968833e+01, 2.53411000e+01, 1.25802167e+01,\n", " 3.98988333e+00, 6.04533333e-01, 1.24500000e-01, 8.16666667e-03,\n", " 3.80000000e-03, 4.36833333e-02, 2.42033333e-01, 8.78816667e-01,\n", " 3.06883333e+00, 9.60745000e+00, 2.27779833e+01, 4.35750333e+01,\n", " 6.89713333e+01, 9.02567000e+01, 9.78938167e+01, 9.10827333e+01,\n", " 7.97067500e+01, 7.93691167e+01, 8.93387000e+01, 1.01714517e+02,\n", " 1.13037867e+02, 1.17581100e+02, 1.07426717e+02, 8.45188833e+01,\n", " 5.85871667e+01, 3.82634500e+01, 2.37392333e+01, 1.27121000e+01,\n", " 4.29471667e+00, 4.43250000e-01, 7.97833333e-02, 1.01666667e-02,\n", " 5.33333333e-04, 1.82500000e-02, 1.22616667e-01, 6.07333333e-01,\n", " 2.91783333e+00, 1.06341667e+01, 2.55538000e+01, 4.75837167e+01,\n", " 7.26322333e+01, 9.16736500e+01, 9.68884167e+01, 9.10977333e+01,\n", " 8.68673000e+01, 9.69665500e+01, 1.11371833e+02, 1.23972067e+02,\n", " 1.29806550e+02, 1.26599550e+02, 1.08880333e+02, 8.11576333e+01,\n", " 5.52258667e+01, 3.72046000e+01, 2.39728000e+01, 1.36437500e+01,\n", " 5.10268333e+00, 5.84700000e-01, 8.29833333e-02, 1.08666667e-02,\n", " 1.88333333e-03, 8.25000000e-03, 5.41666667e-02, 4.66183333e-01,\n", " 3.06558333e+00, 1.23512667e+01, 2.85280667e+01, 5.05083833e+01,\n", " 7.37506167e+01, 9.03691833e+01, 9.50769833e+01, 9.32885333e+01,\n", " 9.78289500e+01, 1.15421317e+02, 1.30267250e+02, 1.39553600e+02,\n", " 1.37100633e+02, 1.28085750e+02, 1.06994517e+02, 7.95539500e+01,\n", " 5.60965667e+01, 3.89430667e+01, 2.55374667e+01, 1.46162500e+01,\n", " 5.72158333e+00, 8.20300000e-01, 9.24500000e-02, 2.21666667e-03,\n", " 7.33333333e-04, 3.86666667e-03, 4.51000000e-02, 5.05583333e-01,\n", " 3.56056667e+00, 1.44081500e+01, 3.09883167e+01, 5.12096333e+01,\n", " 7.14404333e+01, 8.57322167e+01, 9.13810333e+01, 9.42424333e+01,\n", " 1.05047117e+02, 1.23204200e+02, 1.35689433e+02, 1.39110050e+02,\n", " 1.31804500e+02, 1.21436567e+02, 1.01340300e+02, 7.83792667e+01,\n", " 5.82829000e+01, 4.12509333e+01, 2.69801167e+01, 1.48906000e+01,\n", " 5.82828333e+00, 1.07956667e+00, 1.48216667e-01, 1.08333333e-02,\n", " 6.66666667e-04, 3.96666667e-03, 7.43333333e-02, 6.22966667e-01,\n", " 4.46996667e+00, 1.65289667e+01, 3.25549167e+01, 4.99447333e+01,\n", " 6.63117167e+01, 7.78862667e+01, 8.37070500e+01, 8.94484167e+01,\n", " 1.01136017e+02, 1.15857400e+02, 1.26473417e+02, 1.27426650e+02,\n", " 1.21056817e+02, 1.11218100e+02, 9.53723333e+01, 7.73547833e+01,\n", " 5.96073333e+01, 4.20403333e+01, 2.67287667e+01, 1.42431167e+01,\n", " 5.61555000e+00, 1.28710000e+00, 1.91500000e-01, 1.23000000e-02,\n", " 0.00000000e+00, 7.28333333e-03, 1.12200000e-01, 9.53350000e-01,\n", " 5.95223333e+00, 1.85244000e+01, 3.34512000e+01, 4.81763500e+01,\n", " 6.04605333e+01, 6.92180333e+01, 7.46814167e+01, 8.07367000e+01,\n", " 8.95865500e+01, 1.01950417e+02, 1.12616500e+02, 1.15436917e+02,\n", " 1.12244833e+02, 1.04524150e+02, 9.26265833e+01, 7.72614833e+01,\n", " 5.93285167e+01, 4.08083000e+01, 2.49427500e+01, 1.28348000e+01,\n", " 5.15665000e+00, 1.41666667e+00, 2.10033333e-01, 8.88333333e-03,\n", " 1.90000000e-03, 5.31666667e-03, 1.80500000e-01, 1.52015000e+00,\n", " 7.62145000e+00, 2.04178667e+01, 3.49108333e+01, 4.81825667e+01,\n", " 5.82768500e+01, 6.59944667e+01, 7.17466333e+01, 7.65832833e+01,\n", " 8.31222000e+01, 9.51299333e+01, 1.06557200e+02, 1.12201383e+02,\n", " 1.11347933e+02, 1.05018283e+02, 9.36185833e+01, 7.66274333e+01,\n", " 5.67010833e+01, 3.77625667e+01, 2.25467167e+01, 1.13823333e+01,\n", " 4.57905000e+00, 1.29855000e+00, 1.53933333e-01, 1.21833333e-02,\n", " 2.50000000e-04, 1.21833333e-02, 2.86316667e-01, 2.04381667e+00,\n", " 8.72351667e+00, 2.17344667e+01, 3.68331667e+01, 5.09790667e+01,\n", " 6.23501500e+01, 7.12715167e+01, 7.78803000e+01, 8.26346667e+01,\n", " 8.99674333e+01, 1.01406317e+02, 1.12445483e+02, 1.17803450e+02,\n", " 1.15924617e+02, 1.07432500e+02, 9.22773833e+01, 7.18833000e+01,\n", " 5.08002500e+01, 3.26939667e+01, 1.87729667e+01, 9.15635000e+00,\n", " 3.64005000e+00, 1.06850000e+00, 1.46700000e-01, 6.83333333e-03,\n", " 0.00000000e+00, 1.52666667e-02, 3.32000000e-01, 2.25566667e+00,\n", " 8.51305000e+00, 2.06940833e+01, 3.70852167e+01, 5.37940333e+01,\n", " 6.88695000e+01, 8.11596000e+01, 9.04059167e+01, 9.78863000e+01,\n", " 1.06734567e+02, 1.17339517e+02, 1.24952417e+02, 1.25555750e+02,\n", " 1.18216250e+02, 1.03805833e+02, 8.38763833e+01, 6.12356500e+01,\n", " 4.09525000e+01, 2.49440333e+01, 1.36286167e+01, 6.53750000e+00,\n", " 2.71388333e+00, 7.49166667e-01, 1.11683333e-01, 1.68333333e-03,\n", " 5.33333333e-04, 1.27000000e-02, 2.84233333e-01, 1.83920000e+00,\n", " 6.63258333e+00, 1.69004833e+01, 3.28094667e+01, 5.15708833e+01,\n", " 7.04237333e+01, 8.72520000e+01, 1.00985133e+02, 1.12455750e+02,\n", " 1.22594000e+02, 1.30372300e+02, 1.31844900e+02, 1.24868033e+02,\n", " 1.10025800e+02, 8.94660000e+01, 6.65912667e+01, 4.55973833e+01,\n", " 2.85566667e+01, 1.62958167e+01, 8.51148333e+00, 4.10908333e+00,\n", " 1.70298333e+00, 4.43816667e-01, 5.90500000e-02, 6.50000000e-04,\n", " 5.16666667e-04, 9.83333333e-04, 1.87083333e-01, 1.08796667e+00,\n", " 3.94443333e+00, 1.08453667e+01, 2.33906333e+01, 4.06385333e+01,\n", " 6.09691833e+01, 8.10054000e+01, 9.91114333e+01, 1.13100500e+02,\n", " 1.22524317e+02, 1.25302250e+02, 1.20613567e+02, 1.07185867e+02,\n", " 8.77064167e+01, 6.59730500e+01, 4.53337167e+01, 2.87308167e+01,\n", " 1.69034500e+01, 9.16145000e+00, 4.70896667e+00, 2.22501667e+00,\n", " 8.35133333e-01, 1.89116667e-01, 1.78333333e-02, 1.20000000e-03,\n", " 0.00000000e+00, 0.00000000e+00, 6.41666667e-02, 4.18766667e-01,\n", " 1.73270000e+00, 5.01473333e+00, 1.20309167e+01, 2.39401333e+01,\n", " 4.02565833e+01, 5.88924833e+01, 7.72688667e+01, 9.20322000e+01,\n", " 9.97043833e+01, 9.91646667e+01, 9.05921000e+01, 7.55835000e+01,\n", " 5.75861333e+01, 4.01938000e+01, 2.54972333e+01, 1.52398333e+01,\n", " 8.52368333e+00, 4.41923333e+00, 2.20506667e+00, 9.81650000e-01,\n", " 3.10366667e-01, 5.79666667e-02, 9.61666667e-03, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 1.58500000e-02, 1.22200000e-01,\n", " 5.43633333e-01, 1.60085000e+00, 4.20331667e+00, 9.14358333e+00,\n", " 1.68276167e+01, 2.70768167e+01, 3.81033833e+01, 4.70437833e+01,\n", " 5.16087500e+01, 5.09622500e+01, 4.54375833e+01, 3.67445333e+01,\n", " 2.74417833e+01, 1.91085833e+01, 1.21141500e+01, 7.21490000e+00,\n", " 3.95933333e+00, 1.99318333e+00, 9.51233333e-01, 3.99633333e-01,\n", " 1.01816667e-01, 2.21833333e-02, 1.93333333e-03, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 1.56666667e-03, 1.77833333e-02,\n", " 1.27783333e-01, 4.74500000e-01, 1.40550000e+00, 3.18078333e+00,\n", " 6.14340000e+00, 9.82870000e+00, 1.38693333e+01, 1.67183333e+01,\n", " 1.81000167e+01, 1.77754000e+01, 1.58076667e+01, 1.31235500e+01,\n", " 1.04980500e+01, 7.79116667e+00, 5.22193333e+00, 3.16213333e+00,\n", " 1.69133333e+00, 8.25383333e-01, 3.70583333e-01, 1.39816667e-01,\n", " 3.12666667e-02, 3.56666667e-03, 1.73333333e-03, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 6.33333333e-04,\n", " 3.54500000e-02, 1.63083333e-01, 5.38283333e-01, 1.19935000e+00,\n", " 2.31608333e+00, 3.51143333e+00, 4.85021667e+00, 5.98023333e+00,\n", " 6.44481667e+00, 6.25923333e+00, 5.57051667e+00, 4.45076667e+00,\n", " 3.53493333e+00, 2.59181667e+00, 1.70116667e+00, 1.00860000e+00,\n", " 5.40283333e-01, 2.38400000e-01, 7.52666667e-02, 1.61666667e-02,\n", " 5.16666667e-04, 9.83333333e-04, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 2.53333333e-03, 1.55833333e-02, 4.16333333e-02, 8.92000000e-02,\n", " 1.28216667e-01, 1.96733333e-01, 3.36016667e-01, 4.29966667e-01,\n", " 5.25983333e-01, 5.90683333e-01, 6.88033333e-01, 5.92066667e-01,\n", " 4.82733333e-01, 3.43516667e-01, 2.00433333e-01, 8.88666667e-02,\n", " 4.56333333e-02, 1.92833333e-02, 1.51166667e-02, 2.00000000e-03,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00]), variance=array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 2.25932689e-01, 1.85283619e+00, 7.77600000e-01, 1.35000000e-03,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 4.26666667e-03, 3.78831244e-02, 1.11304904e+00, 4.38950014e+00,\n", " 8.77381842e+00, 1.10481753e+01, 2.37100631e+01, 3.05702076e+01,\n", " 3.24179838e+01, 3.24168577e+01, 3.50827272e+01, 3.32481426e+01,\n", " 3.56458167e+01, 2.93051301e+01, 1.87531725e+01, 1.38128227e+01,\n", " 1.02956920e+01, 3.77557306e+00, 1.46710611e+00, 6.50565025e-01,\n", " 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 6.82666667e-02, 1.68331239e-02,\n", " 6.65046115e-01, 2.09323422e-01, 7.11850023e+00, 2.49446945e+01,\n", " 5.09264059e+01, 9.43704957e+01, 1.67196144e+02, 2.41495027e+02,\n", " 3.54210278e+02, 4.82442810e+02, 6.14709179e+02, 6.86303576e+02,\n", " 7.18214160e+02, 6.62129157e+02, 5.41709993e+02, 4.02589090e+02,\n", " 2.33884364e+02, 1.23523350e+02, 5.57731149e+01, 1.56881786e+01,\n", " 6.24861393e+00, 1.21547906e+00, 0.00000000e+00, 0.00000000e+00,\n", " 0.00000000e+00, 0.00000000e+00, 3.62762258e-01, 4.34923026e-01,\n", " 7.29351089e-01, 9.92386468e+00, 3.63433764e+01, 9.85036499e+01,\n", " 2.13020756e+02, 4.23728283e+02, 7.04051837e+02, 1.05901667e+03,\n", " 1.42806129e+03, 1.86577743e+03, 2.28385048e+03, 2.55045016e+03,\n", " 2.49805099e+03, 2.27178434e+03, 1.84900971e+03, 1.34393096e+03,\n", " 8.06831330e+02, 4.42243681e+02, 1.90812088e+02, 7.69947925e+01,\n", " 2.88013923e+01, 3.31905100e+00, 2.80830174e-01, 0.00000000e+00,\n", " 0.00000000e+00, 2.40666667e-02, 4.51530312e-01, 9.28392884e-01,\n", " 1.13933644e+01, 6.64036457e+01, 1.75418888e+02, 4.33617145e+02,\n", " 8.77211049e+02, 1.56846113e+03, 2.48706842e+03, 3.57674413e+03,\n", " 4.80006431e+03, 6.06693177e+03, 7.01962042e+03, 7.47446087e+03,\n", " 7.33762512e+03, 6.62471402e+03, 5.48320171e+03, 4.12934277e+03,\n", " 2.73325705e+03, 1.59557788e+03, 8.23094417e+02, 3.85912075e+02,\n", " 1.48033404e+02, 2.84443973e+01, 4.32794301e+00, 1.24164602e-01,\n", " 0.00000000e+00, 0.00000000e+00, 7.51389423e-01, 8.25424101e+00,\n", " 5.82008428e+01, 2.60558203e+02, 6.59889759e+02, 1.34501473e+03,\n", " 2.42417576e+03, 3.87784856e+03, 5.55792213e+03, 7.35653792e+03,\n", " 9.14288729e+03, 1.06258339e+04, 1.14847482e+04, 1.17716509e+04,\n", " 1.16411075e+04, 1.10480793e+04, 9.78733340e+03, 8.01341605e+03,\n", " 5.88827062e+03, 3.82883825e+03, 2.25642368e+03, 1.21708983e+03,\n", " 5.21272385e+02, 1.27060744e+02, 1.96760013e+01, 3.27816707e-01,\n", " 0.00000000e+00, 1.08331778e-03, 3.08306180e+00, 3.70774852e+01,\n", " 2.00699811e+02, 6.09233045e+02, 1.39431420e+03, 2.67846294e+03,\n", " 4.41350960e+03, 6.48402088e+03, 8.53780731e+03, 1.02978391e+04,\n", " 1.16045627e+04, 1.23253700e+04, 1.25826543e+04, 1.26192850e+04,\n", " 1.26184307e+04, 1.25780356e+04, 1.20715164e+04, 1.07620352e+04,\n", " 8.66220958e+03, 6.09932609e+03, 3.82721655e+03, 2.11294524e+03,\n", " 9.70589047e+02, 3.17710322e+02, 5.94997197e+01, 4.24408598e+00,\n", " 3.68166667e-02, 2.22444767e+00, 1.68312217e+01, 1.01380374e+02,\n", " 4.18734718e+02, 1.10393652e+03, 2.32336023e+03, 4.09367720e+03,\n", " 6.25006349e+03, 8.51367559e+03, 1.03534108e+04, 1.15495347e+04,\n", " 1.20896166e+04, 1.21900223e+04, 1.21952560e+04, 1.21269802e+04,\n", " 1.21497023e+04, 1.22487422e+04, 1.23168078e+04, 1.18010812e+04,\n", " 1.02127085e+04, 7.72352291e+03, 5.01185374e+03, 2.79210156e+03,\n", " 1.27469821e+03, 4.53998739e+02, 8.15798547e+01, 4.29160498e+00,\n", " 6.54827709e-01, 8.60791113e+00, 5.84526585e+01, 2.38798752e+02,\n", " 7.22350769e+02, 1.61833917e+03, 3.14246787e+03, 5.28110667e+03,\n", " 7.75601177e+03, 1.00131172e+04, 1.14997270e+04, 1.21916297e+04,\n", " 1.23453732e+04, 1.24030889e+04, 1.23626581e+04, 1.22771241e+04,\n", " 1.22690290e+04, 1.23255279e+04, 1.24065593e+04, 1.21443314e+04,\n", " 1.09409523e+04, 8.58219908e+03, 5.63759581e+03, 3.00916303e+03,\n", " 1.32126202e+03, 4.66512741e+02, 7.97257563e+01, 4.05124525e+00,\n", " 6.79087634e-01, 1.41714546e+01, 9.33691451e+01, 3.41235325e+02,\n", " 8.73819995e+02, 1.87973394e+03, 3.64012747e+03, 6.09065959e+03,\n", " 8.76602067e+03, 1.08958437e+04, 1.20975810e+04, 1.24210527e+04,\n", " 1.23955496e+04, 1.21239363e+04, 1.18755851e+04, 1.18262471e+04,\n", " 1.19530348e+04, 1.22194551e+04, 1.23512672e+04, 1.20955579e+04,\n", " 1.09367036e+04, 8.62293124e+03, 5.60209927e+03, 2.81396709e+03,\n", " 1.07893707e+03, 3.27117774e+02, 5.55334722e+01, 3.98732028e+00,\n", " 1.33367778e+00, 1.89675341e+01, 9.81173714e+01, 3.29840685e+02,\n", " 8.46129116e+02, 1.88828497e+03, 3.81753651e+03, 6.46018910e+03,\n", " 9.30566629e+03, 1.13078722e+04, 1.21785259e+04, 1.22703476e+04,\n", " 1.16586866e+04, 1.08314849e+04, 1.06004694e+04, 1.10647358e+04,\n", " 1.15367964e+04, 1.20434483e+04, 1.22025761e+04, 1.19072881e+04,\n", " 1.04957093e+04, 8.08391770e+03, 5.15171582e+03, 2.47687978e+03,\n", " 8.33781729e+02, 2.00328075e+02, 3.60422240e+01, 2.48935722e+00,\n", " 7.07276583e-01, 1.35291885e+01, 7.95025656e+01, 2.43785358e+02,\n", " 7.03598486e+02, 1.80011996e+03, 3.89799555e+03, 6.81059373e+03,\n", " 9.77329271e+03, 1.15977902e+04, 1.21419414e+04, 1.18417755e+04,\n", " 1.08283780e+04, 1.00243695e+04, 1.05611770e+04, 1.13398198e+04,\n", " 1.16537511e+04, 1.20851440e+04, 1.21922780e+04, 1.16484851e+04,\n", " 9.80163251e+03, 7.24246850e+03, 4.70172221e+03, 2.36909235e+03,\n", " 7.10409721e+02, 9.78597038e+01, 1.97547290e+01, 8.00979989e-01,\n", " 5.13227447e-01, 7.23689571e+00, 4.42654910e+01, 1.64203868e+02,\n", " 5.80536838e+02, 1.80491114e+03, 4.18265370e+03, 7.37000327e+03,\n", " 1.03045715e+04, 1.18752333e+04, 1.21305451e+04, 1.17046219e+04,\n", " 1.08126961e+04, 1.06193502e+04, 1.18602756e+04, 1.22853428e+04,\n", " 1.20654469e+04, 1.23447393e+04, 1.23757272e+04, 1.13175479e+04,\n", " 9.02391113e+03, 6.62590324e+03, 4.46868308e+03, 2.47727600e+03,\n", " 7.79516251e+02, 7.14073362e+01, 1.37631473e+01, 1.04994747e+00,\n", " 1.70666667e-02, 2.78576337e+00, 2.30409992e+01, 1.13239734e+02,\n", " 5.47847746e+02, 1.98812667e+03, 4.68703162e+03, 7.96613809e+03,\n", " 1.07022561e+04, 1.19833559e+04, 1.21202709e+04, 1.17331777e+04,\n", " 1.13109229e+04, 1.18193989e+04, 1.29536284e+04, 1.24560544e+04,\n", " 1.20885123e+04, 1.25774651e+04, 1.24435365e+04, 1.09608344e+04,\n", " 8.63110930e+03, 6.51580094e+03, 4.54741112e+03, 2.68010250e+03,\n", " 9.62173076e+02, 9.65271014e+01, 1.26101739e+01, 2.15391781e+00,\n", " 2.12816667e-01, 1.06659971e+00, 8.76471205e+00, 8.24552974e+01,\n", " 5.61726378e+02, 2.30040132e+03, 5.21594274e+03, 8.42060011e+03,\n", " 1.08718357e+04, 1.19683829e+04, 1.20023293e+04, 1.17467044e+04,\n", " 1.17103771e+04, 1.24436396e+04, 1.29340916e+04, 1.19952346e+04,\n", " 1.20648603e+04, 1.26290460e+04, 1.23373557e+04, 1.08709820e+04,\n", " 8.82859915e+03, 6.80685897e+03, 4.80610643e+03, 2.85969321e+03,\n", " 1.08895132e+03, 1.41571501e+02, 1.40726375e+01, 1.00713432e-01,\n", " 2.36331894e-02, 8.51865913e-01, 5.84903014e+00, 9.00726034e+01,\n", " 6.42960581e+02, 2.70207840e+03, 5.65155884e+03, 8.54448150e+03,\n", " 1.06580163e+04, 1.17005341e+04, 1.17802965e+04, 1.17407107e+04,\n", " 1.20072170e+04, 1.26806676e+04, 1.26823932e+04, 1.19525229e+04,\n", " 1.24003175e+04, 1.26819112e+04, 1.20658875e+04, 1.08497127e+04,\n", " 9.13551343e+03, 7.18217277e+03, 5.01741808e+03, 2.86291651e+03,\n", " 1.10300155e+03, 1.96439976e+02, 2.50291656e+01, 1.41407287e+00,\n", " 2.66666667e-02, 3.49756762e-01, 1.18415719e+01, 1.05305101e+02,\n", " 8.10387104e+02, 3.09391719e+03, 5.94270633e+03, 8.37599135e+03,\n", " 1.01224299e+04, 1.10407596e+04, 1.12735474e+04, 1.15041495e+04,\n", 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6.05906288e+01, 1.25995134e+02, 2.66374548e+02, 6.45032665e+02,\n", " 2.55155316e+03, 1.20876019e+04, 5.62066898e+04, -3.00000000e+00,\n", " -3.00000000e+00, -3.00000000e+00, 2.64969673e+04, 1.42189583e+04,\n", " 1.94898804e+03, 5.44984922e+02, 1.78364478e+02, 7.59743873e+01,\n", " 3.67128347e+01, 2.10902356e+01, 1.35003293e+01, 1.04150788e+01,\n", " 9.20617748e+00, 9.51888911e+00, 1.12865500e+01, 1.45368980e+01,\n", " 1.93811936e+01, 2.77695496e+01, 4.38808604e+01, 7.60642576e+01,\n", " 1.48846706e+02, 3.09640668e+02, 6.95674525e+02, 1.90953649e+03,\n", " 7.85304026e+03, 3.39092802e+04, 5.99950000e+04, -3.00000000e+00,\n", " -3.00000000e+00, -3.00000000e+00, -3.00000000e+00, 5.99950000e+04,\n", " 8.21910273e+03, 1.56462803e+03, 4.70195075e+02, 2.07074156e+02,\n", " 1.03807719e+02, 6.71251422e+01, 4.71888299e+01, 3.75022510e+01,\n", " 3.42215379e+01, 3.53599051e+01, 4.03234333e+01, 5.21119931e+01,\n", " 6.72496704e+01, 9.29081740e+01, 1.44342314e+02, 2.42528585e+02,\n", " 4.67036763e+02, 1.09733720e+03, 3.70267986e+03, 8.72141146e+03,\n", " 5.86485754e+04, 5.99950000e+04, -3.00000000e+00, -3.00000000e+00,\n", " -3.00000000e+00, -3.00000000e+00, -3.00000000e+00, -3.00000000e+00,\n", " 3.85809078e+04, 1.60842730e+04, 5.44802407e+03, 2.77339788e+03,\n", " 2.05301688e+03, 1.31857925e+03, 7.13944466e+02, 5.84989597e+02,\n", " 4.65854237e+02, 4.29399723e+02, 3.55728102e+02, 4.13883711e+02,\n", " 4.97869713e+02, 7.32993535e+02, 1.27867744e+03, 3.10448916e+03,\n", " 5.31069815e+03, 1.37466342e+04, 1.78353484e+04, 3.01280398e+04,\n", " -3.00000000e+00, -3.00000000e+00, -3.00000000e+00, -3.00000000e+00]))" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from scipy.stats import describe\n", "describe(data_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Как видно, пропусков в данных нет, так что работаем целиком сразу со всем набором." ] }, { "cell_type": "code", "execution_count": 59, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "data = np.corrcoef(data_train, rowvar=False)\n", "plt.imshow(data, cmap='cool')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Посмотрим на график корреляций признаков (чем розовее, тем больше признаки кореллируют). По ощущениям, розовые оттенки есть где то в правом верхнем и левом нижнем углах, но в основном признаки коррелируют несильно." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "В цикле будем перебирать различные количества компонент PCA, чтобы найти наиболее подходящее число\n", "На данном этапе мы решаем задачу кластеризации, то есть обучение без учителя: мы не используем для разметки ответы из y_train, а просто разбиваем выборку на кластеры." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from sklearn.metrics import homogeneity_score" ] }, { "cell_type": "code", "execution_count": 79, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "number of components in pca: 3 , homogeneity score: 0.3510942795554751\n", "number of components in pca: 30 , homogeneity score: 0.490947058193717\n", "number of components in pca: 100 , homogeneity score: 0.49314194189850974\n", "number of components in pca: 300 , homogeneity score: 0.49338453467107996\n", "number of components in pca: 500 , homogeneity score: 0.5051030521327285\n" ] } ], "source": [ "scores = []\n", "pca_numbers = [3, 30, 100, 300, 500] # возможные количества компонент\n", "for comp in pca_numbers:\n", " pca=PCA(n_components=comp)\n", " x_train_pca = pca.fit_transform(data_train) # обучаем PCA для сжатия и одновременно сжимаем data_train\n", " x_test_pca = pca.transform(data_test) # сжимаем data_test\n", " kmeans = KMeans(n_clusters=10, random_state=0).fit(x_train_pca) # обучаем метод\n", " y_pred = kmeans.predict(x_test_pca) # предсказываем кластеры для новых чисел\n", " hs = homogeneity_score(y_test, y_pred) # метрика однородности, она чем больше, тем лучше\n", " print('number of components in pca: ', comp, ', homogeneity score: ', hs)\n", " scores.append([comp, hs])" ] }, { "cell_type": "code", "execution_count": 80, "metadata": {}, "outputs": [], "source": [ "scores = np.array(scores)" ] }, { "cell_type": "code", "execution_count": 81, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.errorbar(scores[:, 0], scores[:, 1], np.var(scores[:, 1]), marker='s', color='coral')\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "pca=PCA(n_components=2)\n", "x_train_pca = pca.fit_transform(data_train) # обучаем PCA для сжатия и одновременно сжимаем data_train\n", "x_test_pca = pca.transform(data_test) # сжимаем data_test\n", "kmeans = KMeans(n_clusters=10, random_state=0).fit(x_train_pca) # обучаем метод\n", "y_pred = kmeans.predict(x_test_pca) # предсказываем кластеры для новых чисел" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "import matplotlib.cm as cm\n", "colors = cm.cool(np.linspace(0, 1, len(y_train)))\n", "plt.scatter(x_train_pca[:, 0], x_train_pca[:, 1], c=y_train, s=50, cmap=cm.rainbow)\n", "\n", "centers = kmeans.cluster_centers_\n", "plt.scatter(centers[:, 0], centers[:, 1], c='black', s=200, alpha=0.5)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Как мы видим, однородность кластеров не достигает достаточно больших значений, и, начиная с 30 компонент, практически не меняется.\n", "Если оценивать график, то можно заметить, что границы классов довольно выражены, хотя некоторые погрешности все же есть и элементы попадают не туда." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Решаем задачу классификации, по сути все тоже самое, только обучение с учителем, то есть мы знаем ответы для x_train и можем их использовать для лучшего обучения. Воспользуемся классификатором логистической регресии." ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "from sklearn.linear_model import LogisticRegression\n", "from sklearn.metrics import accuracy_score" ] }, { "cell_type": "code", "execution_count": 82, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "number of components in pca: 3 , accuracy score: 0.4564\n", "number of components in pca: 10 , accuracy score: 0.7885\n", "number of components in pca: 30 , accuracy score: 0.8871\n", "number of components in pca: 100 , accuracy score: 0.9145\n" ] } ], "source": [ "scores = []\n", "pca_numbers = [3, 10, 30, 100] # возможные количества компонент\n", "for comp in pca_numbers:\n", " pca=PCA(n_components=comp)\n", " x_train_pca = pca.fit_transform(data_train) # обучаем PCA для сжатия и одновременно сжимаем data_train\n", " x_test_pca = pca.transform(data_test) # сжимаем data_test\n", " lr = LogisticRegression()\n", " lr.fit(x_train_pca, y_train) # обучаем метод\n", " y_pred = lr.predict(x_test_pca) # предсказываем классы для новых данных\n", " acs = accuracy_score(y_test, y_pred) # метрика точности, она чем больше, тем лучше\n", " print('number of components in pca: ', comp,', accuracy score: ', acs)\n", " scores.append([comp, acs])" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "scores = np.array(scores)\n", "plt.errorbar(scores[:, 0], scores[:, 1], np.var(scores[:, 1]), marker='s', color='coral')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "С ростом числа компонент растет и точность классификации, которая уже даже на значении 30 принимает неплохие значения. Проверка большего количества компонент занимает длительное время и дает не такой уж большой выигрыш в точности." ] }, { "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": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 2 }